diff --git a/sklearn/neighbors/_binary_tree.pxi b/sklearn/neighbors/_binary_tree.pxi
index 599a4e9cc6426..cf4a77c9f4bed 100755
--- a/sklearn/neighbors/_binary_tree.pxi
+++ b/sklearn/neighbors/_binary_tree.pxi
@@ -1053,9 +1053,13 @@ cdef class BinaryTree:
         if leaf_size < 1:
             raise ValueError("leaf_size must be greater than or equal to 1")
 
+        longest_data = max(len(item) for item in data)
+        if np.any([len(item) < longest_data for item in data]):
+            raise ValueError("Input points must have "
+                             "the same number of dimensions")
+
         n_samples = data.shape[0]
         n_features = data.shape[1]
-
         self.data_arr = np.asarray(data, dtype=DTYPE, order='C')
         self.leaf_size = leaf_size
         self.dist_metric = DistanceMetric.get_metric(metric, **kwargs)
diff --git a/sklearn/neighbors/tests/test_ball_tree.py b/sklearn/neighbors/tests/test_ball_tree.py
index 8da703dbe207d..92fe3ae4f4f39 100644
--- a/sklearn/neighbors/tests/test_ball_tree.py
+++ b/sklearn/neighbors/tests/test_ball_tree.py
@@ -65,3 +65,11 @@ def test_query_haversine():
 
     assert_array_almost_equal(dist1, dist2)
     assert_array_almost_equal(ind1, ind2)
+
+
+def test_different_dimension_size():
+    X = [(1, 2, 3), (2, 5), (5, 5, 1, 2)]
+    Y = np.array(X)
+    msg = ("Input points must have the same number of dimensions")
+    with pytest.raises(ValueError, match=msg):
+        BallTree(Y)