diff --git a/sklearn/ensemble/bagging.py b/sklearn/ensemble/bagging.py
index c2a65d9120e87..4da44bfd0f20d 100644
--- a/sklearn/ensemble/bagging.py
+++ b/sklearn/ensemble/bagging.py
@@ -298,7 +298,7 @@ def _fit(self, X, y, max_samples, max_depth=None, sample_weight=None):
 
         # if max_samples is float:
         if not isinstance(max_samples, (numbers.Integral, np.integer)):
-            max_samples = int(self.max_samples * X.shape[0])
+            max_samples = int(max_samples * X.shape[0])
 
         if not (0 < max_samples <= X.shape[0]):
             raise ValueError("max_samples must be in (0, n_samples]")