diff --git a/GPy/core/gp.py b/GPy/core/gp.py
index 7a29664f..92b859dc 100644
--- a/GPy/core/gp.py
+++ b/GPy/core/gp.py
@@ -395,9 +395,9 @@ class GP(Model):
             var_jac = compute_cov_inner(self.posterior.woodbury_inv)
         return mean_jac, var_jac
 
-    def predict_wishard_embedding(self, Xnew, kern=None, mean=True, covariance=True):
+    def predict_wishart_embedding(self, Xnew, kern=None, mean=True, covariance=True):
         """
-        Predict the wishard embedding G of the GP. This is the density of the
+        Predict the wishart embedding G of the GP. This is the density of the
         input of the GP defined by the probabilistic function mapping f.
         G = J_mean.T*J_mean + output_dim*J_cov.
 
@@ -425,6 +425,10 @@ class GP(Model):
             G += Sigma
         return G
 
+    def predict_wishard_embedding(self, Xnew, kern=None, mean=True, covariance=True):
+        warnings.warn("Wrong naming, use predict_wishart_embedding instead. Will be removed in future versions!", DeprecationWarning)
+        return self.predict_wishart_embedding(Xnew, kern, mean, covariance)
+
     def predict_magnification(self, Xnew, kern=None, mean=True, covariance=True):
         """
         Predict the magnification factor as