diff --git a/sklearn/ensemble/_bagging.py b/sklearn/ensemble/_bagging.py
index 58104d23fcf4e..070bc374f3123 100644
--- a/sklearn/ensemble/_bagging.py
+++ b/sklearn/ensemble/_bagging.py
@@ -488,7 +488,7 @@ class BaggingClassifier(ClassifierMixin, BaseBagging):
 
     oob_score : bool, default=False
         Whether to use out-of-bag samples to estimate
-        the generalization error.
+        the generalization error. Only available if bootstrap=True.
 
     warm_start : bool, default=False
         When set to True, reuse the solution of the previous call to fit
@@ -897,7 +897,7 @@ class BaggingRegressor(RegressorMixin, BaseBagging):
 
     oob_score : bool, default=False
         Whether to use out-of-bag samples to estimate
-        the generalization error.
+        the generalization error. Only available if bootstrap=True.
 
     warm_start : bool, default=False
         When set to True, reuse the solution of the previous call to fit
diff --git a/sklearn/ensemble/_forest.py b/sklearn/ensemble/_forest.py
index c97b5b9f12528..c0b190c60ef54 100644
--- a/sklearn/ensemble/_forest.py
+++ b/sklearn/ensemble/_forest.py
@@ -1075,6 +1075,7 @@ class RandomForestClassifier(ForestClassifier):
 
     oob_score : bool, default=False
         Whether to use out-of-bag samples to estimate the generalization score.
+        Only available if bootstrap=True.
 
     n_jobs : int, default=None
         The number of jobs to run in parallel. :meth:`fit`, :meth:`predict`,
@@ -1398,6 +1399,7 @@ class RandomForestRegressor(ForestRegressor):
 
     oob_score : bool, default=False
         Whether to use out-of-bag samples to estimate the generalization score.
+        Only available if bootstrap=True.
 
     n_jobs : int, default=None
         The number of jobs to run in parallel. :meth:`fit`, :meth:`predict`,
@@ -1680,6 +1682,7 @@ class ExtraTreesClassifier(ForestClassifier):
 
     oob_score : bool, default=False
         Whether to use out-of-bag samples to estimate the generalization score.
+        Only available if bootstrap=True.
 
     n_jobs : int, default=None
         The number of jobs to run in parallel. :meth:`fit`, :meth:`predict`,
@@ -1999,6 +2002,7 @@ class ExtraTreesRegressor(ForestRegressor):
 
     oob_score : bool, default=False
         Whether to use out-of-bag samples to estimate the generalization score.
+        Only available if bootstrap=True.
 
     n_jobs : int, default=None
         The number of jobs to run in parallel. :meth:`fit`, :meth:`predict`,