diff --git a/chainladder/methods/chainladder.py b/chainladder/methods/chainladder.py
index cd69eb10..ca5df449 100644
--- a/chainladder/methods/chainladder.py
+++ b/chainladder/methods/chainladder.py
@@ -49,7 +49,7 @@ def fit(self, X, y=None, sample_weight=None):
         return self
 
     def predict(self, X, sample_weight=None):
-        """Predicts the Benktander ultimate on a new triangle **X**
+        """Predicts the chainladder ultimate on a new triangle **X**
 
         Parameters
         ----------
@@ -61,7 +61,7 @@ def predict(self, X, sample_weight=None):
         Returns
         -------
         X_new: Triangle
-            Loss data with Benktander ultimate applied
+            Loss data with chainladder ultimate applied
         """
         X_new = super().predict(X, sample_weight)
         X_new.ultimate_ = self._get_ultimate(X_new, sample_weight)
diff --git a/chainladder/methods/expectedloss.py b/chainladder/methods/expectedloss.py
index 6ce83970..ea09cc99 100644
--- a/chainladder/methods/expectedloss.py
+++ b/chainladder/methods/expectedloss.py
@@ -39,7 +39,7 @@ def __init__(self, apriori=1.0, apriori_sigma=0.0, random_state=None):
         self.random_state = random_state
 
     def fit(self, X, y=None, sample_weight=None):
-        """Applies the Bornhuetter-Ferguson technique to triangle **X**
+        """Applies the Benktander technique to triangle **X**
 
         Parameters
         ----------
@@ -60,7 +60,7 @@ def fit(self, X, y=None, sample_weight=None):
         return self
 
     def predict(self, X, sample_weight=None):
-        """Predicts the Bornhuetter-Ferguson ultimate on a new triangle **X**
+        """Predicts the Benktander ultimate on a new triangle **X**
 
         Parameters
         ----------