diff --git a/ax/modelbridge/tests/test_generation_node.py b/ax/modelbridge/tests/test_generation_node.py
index b682490f65b..9667f808ddc 100644
--- a/ax/modelbridge/tests/test_generation_node.py
+++ b/ax/modelbridge/tests/test_generation_node.py
@@ -314,7 +314,8 @@ def test_node_string_representation(self) -> None:
                 "'not_in_statuses': None, 'transition_to': None, "
                 "'block_transition_if_unmet': True, 'block_gen_if_met': False, "
                 "'use_all_trials_in_exp': False, "
-                "'continue_trial_generation': False})])"
+                "'continue_trial_generation': False, "
+                "'count_only_trials_with_data': False})])"
             ),
         )
 
diff --git a/ax/modelbridge/tests/test_generation_node_input_constructors.py b/ax/modelbridge/tests/test_generation_node_input_constructors.py
index 732de6a1338..3c4ae6ac2e4 100644
--- a/ax/modelbridge/tests/test_generation_node_input_constructors.py
+++ b/ax/modelbridge/tests/test_generation_node_input_constructors.py
@@ -113,7 +113,6 @@ def test_all_constructors_have_expected_signature_for_purpose(self) -> None:
                     untested_constructors.remove(constructor)
 
         # There should be no untested constructors left.
-        print(untested_constructors)
         self.assertEqual(len(untested_constructors), 0)
 
     def test_consume_all_n_constructor(self) -> None:
diff --git a/ax/modelbridge/tests/test_transition_criterion.py b/ax/modelbridge/tests/test_transition_criterion.py
index 78ca0e50032..3dc5e334890 100644
--- a/ax/modelbridge/tests/test_transition_criterion.py
+++ b/ax/modelbridge/tests/test_transition_criterion.py
@@ -580,7 +580,8 @@ def test_repr(self) -> None:
             + "'block_transition_if_unmet': False, "
             + "'block_gen_if_met': True, "
             + "'use_all_trials_in_exp': False, "
-            + "'continue_trial_generation': False})",
+            + "'continue_trial_generation': False, "
+            + "'count_only_trials_with_data': False})",
         )
         minimum_trials_in_status_criterion = MinTrials(
             only_in_statuses=[TrialStatus.COMPLETED, TrialStatus.EARLY_STOPPED],
@@ -599,7 +600,8 @@ def test_repr(self) -> None:
             + "'block_transition_if_unmet': False, "
             + "'block_gen_if_met': True, "
             + "'use_all_trials_in_exp': False, "
-            + "'continue_trial_generation': False})",
+            + "'continue_trial_generation': False, "
+            + "'count_only_trials_with_data': False})",
         )
         minimum_preference_occurrences_criterion = MinimumPreferenceOccurances(
             metric_name="m1", threshold=3
diff --git a/ax/modelbridge/transition_criterion.py b/ax/modelbridge/transition_criterion.py
index 7727a33fc80..19e44906fa9 100644
--- a/ax/modelbridge/transition_criterion.py
+++ b/ax/modelbridge/transition_criterion.py
@@ -31,7 +31,6 @@
 
 
 class TransitionCriterion(SortableBase, SerializationMixin):
-    # TODO: @mgarrard rename to ActionCriterion
     """
     Simple class to describe a condition which must be met for this GenerationNode to
     take an action such as generation, transition, etc.
@@ -262,6 +261,8 @@ class TrialBasedCriterion(TransitionCriterion):
             batch from different ``GenerationNodes``. This flag should be set to
             True for the last node in a set of ``GenerationNodes`` expected to
             create a given ``BatchTrial``.
+        count_only_trials_with_data: If set to True, only trials with data will be
+            counted towards the ``threshold``. Defaults to False.
     """
 
     def __init__(
@@ -274,11 +275,13 @@ def __init__(
         transition_to: str | None = None,
         use_all_trials_in_exp: bool | None = False,
         continue_trial_generation: bool | None = False,
+        count_only_trials_with_data: bool = False,
     ) -> None:
         self.threshold = threshold
         self.only_in_statuses = only_in_statuses
         self.not_in_statuses = not_in_statuses
         self.use_all_trials_in_exp = use_all_trials_in_exp
+        self.count_only_trials_with_data = count_only_trials_with_data
         super().__init__(
             transition_to=transition_to,
             block_transition_if_unmet=block_transition_if_unmet,
@@ -334,6 +337,14 @@ def num_contributing_to_threshold(
             trials_from_node: The set of trials generated by this GenerationNode.
         """
         all_trials_to_check = self.all_trials_to_check(experiment=experiment)
+        if self.count_only_trials_with_data:
+            all_trials_to_check = {
+                trial_index
+                for trial_index in all_trials_to_check
+                # TODO[@mgarrard]: determine if we need to actually check data with
+                # more granularity, e.g. number of days of data, etc.
+                if trial_index in experiment.data_by_trial
+            }
         # Some criteria may rely on experiment level data, instead of only trials
         # generated from the node associated with the criterion.
         if self.use_all_trials_in_exp:
@@ -415,6 +426,8 @@ class MaxGenerationParallelism(TrialBasedCriterion):
             create a given ``BatchTrial``. Defaults to False for
             MaxGenerationParallelism since this criterion isn't currently used for
             node -> node or trial -> trial transition.
+        count_only_trials_with_data: If set to True, only trials with data will be
+            counted towards the ``threshold``. Defaults to False.
     """
 
     def __init__(
@@ -497,6 +510,8 @@ class MaxTrials(TrialBasedCriterion):
             batch from different ``GenerationNodes``. This flag should be set to
             True for the last node in a set of ``GenerationNodes`` expected to
             create a given ``BatchTrial``.
+        count_only_trials_with_data: If set to True, only trials with data will be
+            counted towards the ``threshold``. Defaults to False.
     """
 
     def __init__(
@@ -509,6 +524,7 @@ def __init__(
         block_gen_if_met: bool | None = False,
         use_all_trials_in_exp: bool | None = False,
         continue_trial_generation: bool | None = False,
+        count_only_trials_with_data: bool = False,
     ) -> None:
         super().__init__(
             threshold=threshold,
@@ -519,6 +535,7 @@ def __init__(
             block_transition_if_unmet=block_transition_if_unmet,
             use_all_trials_in_exp=use_all_trials_in_exp,
             continue_trial_generation=continue_trial_generation,
+            count_only_trials_with_data=count_only_trials_with_data,
         )
 
     def block_continued_generation_error(
@@ -573,6 +590,8 @@ class MinTrials(TrialBasedCriterion):
             batch from different ``GenerationNodes``. This flag should be set to
             True for the last node in a set of ``GenerationNodes`` expected to
             create a given ``BatchTrial``.
+        count_only_trials_with_data: If set to True, only trials with data will be
+            counted towards the ``threshold``. Defaults to False.
     """
 
     def __init__(
@@ -585,6 +604,7 @@ def __init__(
         block_gen_if_met: bool | None = False,
         use_all_trials_in_exp: bool | None = False,
         continue_trial_generation: bool | None = False,
+        count_only_trials_with_data: bool = False,
     ) -> None:
         super().__init__(
             threshold=threshold,
@@ -595,6 +615,7 @@ def __init__(
             block_transition_if_unmet=block_transition_if_unmet,
             use_all_trials_in_exp=use_all_trials_in_exp,
             continue_trial_generation=continue_trial_generation,
+            count_only_trials_with_data=count_only_trials_with_data,
         )
 
     def block_continued_generation_error(