diff --git a/src/aws_durable_execution_sdk_python/concurrency.py b/src/aws_durable_execution_sdk_python/concurrency.py
index b5af8c6..3cf2aa1 100644
--- a/src/aws_durable_execution_sdk_python/concurrency.py
+++ b/src/aws_durable_execution_sdk_python/concurrency.py
@@ -7,6 +7,7 @@
 import threading
 import time
 from abc import ABC, abstractmethod
+from collections import Counter
 from concurrent.futures import Future, ThreadPoolExecutor
 from dataclasses import dataclass
 from enum import Enum
@@ -22,7 +23,7 @@
 from aws_durable_execution_sdk_python.types import BatchResult as BatchResultProtocol
 
 if TYPE_CHECKING:
-    from collections.abc import Callable
+    from collections.abc import Callable, Iterable
 
     from aws_durable_execution_sdk_python.config import CompletionConfig
     from aws_durable_execution_sdk_python.lambda_service import OperationSubType
@@ -67,6 +68,42 @@ def suspend(exception: SuspendExecution) -> SuspendResult:
         return SuspendResult(should_suspend=True, exception=exception)
 
 
+def _get_completion_reason(
+    items: Iterable[BatchItemStatus], completion_config: CompletionConfig | None = None
+) -> CompletionReason:
+    """
+    Infer completion reason based on batch item statuses and completion config.
+
+    This follows the same logic as the TypeScript implementation:
+    - If all items completed: ALL_COMPLETED
+    - If minSuccessful threshold met and not all completed: MIN_SUCCESSFUL_REACHED
+    - Otherwise: FAILURE_TOLERANCE_EXCEEDED
+    """
+
+    counts = Counter(items)
+    succeeded_count = counts.get(BatchItemStatus.SUCCEEDED, 0)
+    failed_count = counts.get(BatchItemStatus.FAILED, 0)
+    started_count = counts.get(BatchItemStatus.STARTED, 0)
+
+    completed_count = succeeded_count + failed_count
+    total_count = started_count + completed_count
+
+    # If all items completed (no started items), it's ALL_COMPLETED
+    if completed_count == total_count:
+        return CompletionReason.ALL_COMPLETED
+
+    # If we have completion config and minSuccessful threshold is met
+    if (
+        completion_config
+        and (min_successful := completion_config.min_successful) is not None
+        and succeeded_count >= min_successful
+    ):
+        return CompletionReason.MIN_SUCCESSFUL_REACHED
+
+    # Otherwise, assume failure tolerance was exceeded
+    return CompletionReason.FAILURE_TOLERANCE_EXCEEDED
+
+
 @dataclass(frozen=True)
 class BatchItem(Generic[R]):
     index: int
@@ -98,16 +135,44 @@ class BatchResult(Generic[R], BatchResultProtocol[R]):  # noqa: PYI059
     completion_reason: CompletionReason
 
     @classmethod
-    def from_dict(cls, data: dict) -> BatchResult[R]:
+    def from_dict(
+        cls, data: dict, completion_config: CompletionConfig | None = None
+    ) -> BatchResult[R]:
         batch_items: list[BatchItem[R]] = [
             BatchItem.from_dict(item) for item in data["all"]
         ]
-        # TODO: is this valid? assuming completion reason is ALL_COMPLETED?
-        completion_reason = CompletionReason(
-            data.get("completionReason", "ALL_COMPLETED")
-        )
+
+        completion_reason_value = data.get("completionReason")
+        if completion_reason_value is None:
+            # Infer completion reason from batch item statuses and completion config
+            # This aligns with the TypeScript implementation that uses completion config
+            # to accurately reconstruct the completion reason during replay
+            result = cls.from_items(batch_items, completion_config)
+            logger.warning(
+                "Missing completionReason in BatchResult deserialization, "
+                "inferred '%s' from batch item statuses. "
+                "This may indicate incomplete serialization data.",
+                result.completion_reason.value,
+            )
+            return result
+
+        completion_reason = CompletionReason(completion_reason_value)
         return cls(batch_items, completion_reason)
 
+    @classmethod
+    def from_items(
+        cls,
+        items: Iterable[BatchItem[R]],
+        completion_config: CompletionConfig | None = None,
+    ):
+        items = list(items)
+        # Infer completion reason from batch item statuses and completion config
+        # This aligns with the TypeScript implementation that uses completion config
+        # to accurately reconstruct the completion reason during replay
+        statuses = (item.status for item in items)
+        completion_reason = _get_completion_reason(statuses, completion_config)
+        return cls(items, completion_reason)
+
     def to_dict(self) -> dict:
         return {
             "all": [item.to_dict() for item in self.all],
@@ -163,19 +228,15 @@ def get_errors(self) -> list[ErrorObject]:
 
     @property
     def success_count(self) -> int:
-        return len(
-            [item for item in self.all if item.status is BatchItemStatus.SUCCEEDED]
-        )
+        return sum(1 for item in self.all if item.status is BatchItemStatus.SUCCEEDED)
 
     @property
     def failure_count(self) -> int:
-        return len([item for item in self.all if item.status is BatchItemStatus.FAILED])
+        return sum(1 for item in self.all if item.status is BatchItemStatus.FAILED)
 
     @property
     def started_count(self) -> int:
-        return len(
-            [item for item in self.all if item.status is BatchItemStatus.STARTED]
-        )
+        return sum(1 for item in self.all if item.status is BatchItemStatus.STARTED)
 
     @property
     def total_count(self) -> int:
@@ -336,25 +397,66 @@ def fail_task(self) -> None:
         with self._lock:
             self.failure_count += 1
 
-    def should_complete(self) -> bool:
-        """Check if execution should complete."""
+    def should_continue(self) -> bool:
+        """
+        Check if we should continue starting new tasks (based on failure tolerance).
+        Matches TypeScript shouldContinue() logic.
+        """
         with self._lock:
-            # Success condition
-            if self.success_count >= self.min_successful:
-                return True
+            # If no completion config, only continue if no failures
+            if (
+                self.tolerated_failure_count is None
+                and self.tolerated_failure_percentage is None
+            ):
+                return self.failure_count == 0
 
-            # Failure conditions
-            if self._is_failure_condition_reached(
-                tolerated_count=self.tolerated_failure_count,
-                tolerated_percentage=self.tolerated_failure_percentage,
-                failure_count=self.failure_count,
+            # Check failure count tolerance
+            if (
+                self.tolerated_failure_count is not None
+                and self.failure_count > self.tolerated_failure_count
             ):
+                return False
+
+            # Check failure percentage tolerance
+            if self.tolerated_failure_percentage is not None and self.total_tasks > 0:
+                failure_percentage = (self.failure_count / self.total_tasks) * 100
+                if failure_percentage > self.tolerated_failure_percentage:
+                    return False
+
+            return True
+
+    def is_complete(self) -> bool:
+        """
+        Check if execution should complete (based on completion criteria).
+        Matches TypeScript isComplete() logic.
+        """
+        with self._lock:
+            completed_count = self.success_count + self.failure_count
+
+            # All tasks completed
+            if completed_count == self.total_tasks:
+                # Complete if no failure tolerance OR no failures OR min successful reached
+                return (
+                    (
+                        self.tolerated_failure_count is None
+                        and self.tolerated_failure_percentage is None
+                    )
+                    or self.failure_count == 0
+                    or self.success_count >= self.min_successful
+                )
+
+            # Min successful reached (even if not all tasks completed)
+            if self.success_count >= self.min_successful:
                 return True
 
-            # Impossible to succeed condition
-            # TODO: should this keep running? TS doesn't currently handle this either.
-            remaining_tasks = self.total_tasks - self.success_count - self.failure_count
-            return self.success_count + remaining_tasks < self.min_successful
+            return False
+
+    def should_complete(self) -> bool:
+        """
+        Check if execution should complete.
+        Combines TypeScript shouldContinue() and isComplete() logic.
+        """
+        return self.is_complete() or not self.should_continue()
 
     def is_all_completed(self) -> bool:
         """True if all tasks completed successfully."""
@@ -663,15 +765,9 @@ def _create_result(self) -> BatchResult[ResultType]:
                     )
                 )
 
-        completion_reason: CompletionReason = (
-            CompletionReason.ALL_COMPLETED
-            if self.counters.is_all_completed()
-            else (
-                CompletionReason.MIN_SUCCESSFUL_REACHED
-                if self.counters.is_min_successful_reached()
-                else CompletionReason.FAILURE_TOLERANCE_EXCEEDED
-            )
-        )
+        # Use the same completion reason logic as _get_completion_reason for consistency
+        statuses = (item.status for item in batch_items)
+        completion_reason = _get_completion_reason(statuses, self.completion_config)
 
         return BatchResult(batch_items, completion_reason)
 
diff --git a/tests/concurrency_test.py b/tests/concurrency_test.py
index 38dc9d6..11c2d64 100644
--- a/tests/concurrency_test.py
+++ b/tests/concurrency_test.py
@@ -319,8 +319,178 @@ def test_batch_result_from_dict_default_completion_reason():
         # No completionReason provided
     }
 
-    result = BatchResult.from_dict(data)
-    assert result.completion_reason == CompletionReason.ALL_COMPLETED
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data)
+        assert result.completion_reason == CompletionReason.ALL_COMPLETED
+        # Verify warning was logged
+        mock_logger.warning.assert_called_once()
+        assert "Missing completionReason" in mock_logger.warning.call_args[0][0]
+
+
+def test_batch_result_from_dict_infer_all_completed_all_succeeded():
+    """Test BatchResult from_dict infers ALL_COMPLETED when all items succeeded."""
+    data = {
+        "all": [
+            {"index": 0, "status": "SUCCEEDED", "result": "result1", "error": None},
+            {"index": 1, "status": "SUCCEEDED", "result": "result2", "error": None},
+        ],
+        # No completionReason provided
+    }
+
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data)
+        assert result.completion_reason == CompletionReason.ALL_COMPLETED
+        mock_logger.warning.assert_called_once()
+
+
+def test_batch_result_from_dict_infer_failure_tolerance_exceeded_all_failed():
+    """Test BatchResult from_dict infers FAILURE_TOLERANCE_EXCEEDED when all items failed."""
+    error_data = {
+        "message": "Test error",
+        "type": "TestError",
+        "data": None,
+        "stackTrace": None,
+    }
+    data = {
+        "all": [
+            {"index": 0, "status": "FAILED", "result": None, "error": error_data},
+            {"index": 1, "status": "FAILED", "result": None, "error": error_data},
+        ],
+        # No completionReason provided
+    }
+
+    # even if everything has failed, if we've completed all items, then we've finished as ALL_COMPLETED
+    # https://github.com/aws/aws-durable-execution-sdk-js/blob/f20396f24afa9d6539d8e5056ee851ac7ef62301/packages/aws-durable-execution-sdk-js/src/handlers/concurrent-execution-handler/concurrent-execution-handler.ts#L324-L335
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data)
+        assert result.completion_reason == CompletionReason.ALL_COMPLETED
+        mock_logger.warning.assert_called_once()
+
+
+def test_batch_result_from_dict_infer_all_completed_mixed_success_failure():
+    """Test BatchResult from_dict infers ALL_COMPLETED when mix of success/failure but no started items."""
+    error_data = {
+        "message": "Test error",
+        "type": "TestError",
+        "data": None,
+        "stackTrace": None,
+    }
+    data = {
+        "all": [
+            {"index": 0, "status": "SUCCEEDED", "result": "result1", "error": None},
+            {"index": 1, "status": "FAILED", "result": None, "error": error_data},
+            {"index": 2, "status": "SUCCEEDED", "result": "result2", "error": None},
+        ],
+        # No completionReason provided
+    }
+
+    # the logic is that when \every item i: hasCompleted(i) then terminate due to all_completed
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data)
+        assert result.completion_reason == CompletionReason.ALL_COMPLETED
+        mock_logger.warning.assert_called_once()
+
+
+def test_batch_result_from_dict_infer_min_successful_reached_has_started():
+    """Test BatchResult from_dict infers MIN_SUCCESSFUL_REACHED when items are still started."""
+    data = {
+        "all": [
+            {"index": 0, "status": "SUCCEEDED", "result": "result1", "error": None},
+            {"index": 1, "status": "STARTED", "result": None, "error": None},
+            {"index": 2, "status": "SUCCEEDED", "result": "result2", "error": None},
+        ],
+        # No completionReason provided
+    }
+
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data, CompletionConfig(1))
+        assert result.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+        mock_logger.warning.assert_called_once()
+
+
+def test_batch_result_from_dict_infer_empty_items():
+    """Test BatchResult from_dict infers ALL_COMPLETED for empty items."""
+    data = {
+        "all": [],
+        # No completionReason provided
+    }
+
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data)
+        assert result.completion_reason == CompletionReason.ALL_COMPLETED
+        mock_logger.warning.assert_called_once()
+
+
+def test_batch_result_from_dict_with_explicit_completion_reason():
+    """Test BatchResult from_dict uses explicit completionReason when provided."""
+    data = {
+        "all": [
+            {"index": 0, "status": "SUCCEEDED", "result": "result1", "error": None}
+        ],
+        "completionReason": "MIN_SUCCESSFUL_REACHED",
+    }
+
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data)
+        assert result.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+        # No warning should be logged when completionReason is provided
+        mock_logger.warning.assert_not_called()
+
+
+def test_batch_result_infer_completion_reason_edge_cases():
+    """Test _infer_completion_reason method with various edge cases."""
+    # Test with only started items
+    started_items = [
+        BatchItem(0, BatchItemStatus.STARTED).to_dict(),
+        BatchItem(1, BatchItemStatus.STARTED).to_dict(),
+    ]
+    items = {"all": started_items}
+    batch = BatchResult.from_dict(items, CompletionConfig(0))  # SLF001
+    # this state is not possible with CompletionConfig(0)
+    assert batch.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+
+    # Test with only started items
+    started_items = [
+        BatchItem(0, BatchItemStatus.STARTED).to_dict(),
+        BatchItem(1, BatchItemStatus.STARTED).to_dict(),
+    ]
+    items = {"all": started_items}
+    batch = BatchResult.from_dict(items)  # SLF001
+    # this state is not possible with CompletionConfig(0)
+    assert batch.completion_reason == CompletionReason.FAILURE_TOLERANCE_EXCEEDED
+
+    # Test with only failed items
+    failed_items = [
+        BatchItem(
+            0, BatchItemStatus.FAILED, error=ErrorObject("msg", "Error", None, None)
+        ).to_dict(),
+        BatchItem(
+            1, BatchItemStatus.FAILED, error=ErrorObject("msg", "Error", None, None)
+        ).to_dict(),
+    ]
+    failed_items = {"all": failed_items}
+    batch = BatchResult.from_dict(failed_items)  # SLF001
+    assert batch.completion_reason == CompletionReason.ALL_COMPLETED
+
+    # Test with only succeeded items
+    succeeded_items = [
+        BatchItem(0, BatchItemStatus.SUCCEEDED, "result1").to_dict(),
+        BatchItem(1, BatchItemStatus.SUCCEEDED, "result2").to_dict(),
+    ]
+    succeeded_items = {"all": succeeded_items}
+    batch = BatchResult.from_dict(succeeded_items)  # SLF001
+    assert batch.completion_reason == CompletionReason.ALL_COMPLETED
+
+    # Test with mixed but no started (all completed)
+    mixed_items = [
+        BatchItem(0, BatchItemStatus.SUCCEEDED, "result1"),
+        BatchItem(
+            1, BatchItemStatus.FAILED, error=ErrorObject("msg", "Error", None, None)
+        ),
+    ]
+
+    batch = BatchResult.from_items(mixed_items)  # SLF001
+    assert batch.completion_reason == CompletionReason.ALL_COMPLETED
 
 
 def test_batch_result_get_results_empty():
@@ -924,7 +1094,10 @@ def mock_run_in_child_context(func, name, config):
     assert len(result.all) == 2
     assert result.all[0].status == BatchItemStatus.SUCCEEDED
     assert result.all[1].status == BatchItemStatus.FAILED
-    assert result.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+    # WHEN all items complete, THEN completion reason is ALL_COMPLETED.
+    # we don't consider thresholds and limits.
+    # https://github.com/aws/aws-durable-execution-sdk-js/blob/ff8b72ef888dd47a840f36d4eb0ee84dd3b55a30/packages/aws-durable-execution-sdk-js/src/handlers/concurrent-execution-handler/concurrent-execution-handler.test.ts#L630-L655
+    assert result.completion_reason == CompletionReason.ALL_COMPLETED
 
 
 def test_concurrent_executor_execute_item_in_child_context():
@@ -1007,7 +1180,10 @@ def mock_run_in_child_context(func, name, config):
         return func(Mock())
 
     result = executor.execute(execution_state, mock_run_in_child_context)
-    assert result.completion_reason == CompletionReason.FAILURE_TOLERANCE_EXCEEDED
+    # WHEN all items complete, THEN completion reason is ALL_COMPLETED.
+    # we don't consider thresholds and limits.
+    # https://github.com/aws/aws-durable-execution-sdk-js/blob/ff8b72ef888dd47a840f36d4eb0ee84dd3b55a30/packages/aws-durable-execution-sdk-js/src/handlers/concurrent-execution-handler/concurrent-execution-handler.test.ts#L630-L655
+    assert result.completion_reason == CompletionReason.ALL_COMPLETED
 
 
 def test_single_task_suspend_bubbles_up():
@@ -1692,3 +1868,94 @@ def test_timer_scheduler_future_time_condition_false():
 
         # Callback should not be called since time is in future
         callback.assert_not_called()
+
+
+def test_batch_result_from_dict_with_completion_config():
+    """Test BatchResult from_dict with completion config parameter."""
+    data = {
+        "all": [
+            {"index": 0, "status": "SUCCEEDED", "result": "result1", "error": None},
+            {"index": 1, "status": "STARTED", "result": None, "error": None},
+        ],
+        # No completionReason provided
+    }
+
+    # With started items, should infer MIN_SUCCESSFUL_REACHED
+    completion_config = CompletionConfig(min_successful=1)
+
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data, completion_config)
+        assert result.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+        mock_logger.warning.assert_called_once()
+
+
+def test_batch_result_from_dict_all_completed():
+    """Test BatchResult from_dict infers ALL_COMPLETED when all items are completed."""
+    data = {
+        "all": [
+            {"index": 0, "status": "SUCCEEDED", "result": "result1", "error": None},
+            {
+                "index": 1,
+                "status": "FAILED",
+                "result": None,
+                "error": {
+                    "message": "error",
+                    "type": "Error",
+                    "data": None,
+                    "stackTrace": None,
+                },
+            },
+        ],
+        # No completionReason provided
+    }
+
+    with patch("aws_durable_execution_sdk_python.concurrency.logger") as mock_logger:
+        result = BatchResult.from_dict(data)
+        assert result.completion_reason == CompletionReason.ALL_COMPLETED
+        mock_logger.warning.assert_called_once()
+
+
+def test_batch_result_from_dict_backward_compatibility():
+    """Test BatchResult from_dict maintains backward compatibility when no completion_config provided."""
+    data = {
+        "all": [
+            {"index": 0, "status": "SUCCEEDED", "result": "result1", "error": None}
+        ],
+        "completionReason": "MIN_SUCCESSFUL_REACHED",
+    }
+
+    # Should work without completion_config parameter
+    result = BatchResult.from_dict(data)
+    assert result.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+
+    # Should also work with None completion_config
+    result2 = BatchResult.from_dict(data, None)
+    assert result2.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+
+
+def test_batch_result_infer_completion_reason_basic_cases():
+    """Test _infer_completion_reason method with basic scenarios."""
+    # Test with started items - should be MIN_SUCCESSFUL_REACHED
+    items = {
+        "all": [
+            BatchItem(0, BatchItemStatus.SUCCEEDED, "result1").to_dict(),
+            BatchItem(1, BatchItemStatus.STARTED).to_dict(),
+        ]
+    }
+    batch = BatchResult.from_dict(items, CompletionConfig(1))
+    assert batch.completion_reason == CompletionReason.MIN_SUCCESSFUL_REACHED
+
+    # Test with all completed items - should be ALL_COMPLETED
+    completed_items = [
+        BatchItem(0, BatchItemStatus.SUCCEEDED, "result1").to_dict(),
+        BatchItem(
+            1, BatchItemStatus.FAILED, error=ErrorObject("msg", "Error", None, None)
+        ).to_dict(),
+    ]
+    completed_items = {"all": completed_items}
+    batch = BatchResult.from_dict(completed_items, CompletionConfig(1))
+    assert batch.completion_reason == CompletionReason.ALL_COMPLETED
+
+    # Test empty items - should be ALL_COMPLETED
+    batch = BatchResult.from_dict({"all": []}, CompletionConfig(1))
+    assert batch.completion_reason == CompletionReason.ALL_COMPLETED