diff --git a/icu_benchmarks/recipes/recipe.py b/icu_benchmarks/recipes/recipe.py
index fb722806..b10e8522 100644
--- a/icu_benchmarks/recipes/recipe.py
+++ b/icu_benchmarks/recipes/recipe.py
@@ -51,30 +51,38 @@ def _apply_group(self, data, step):
             data = data.groupby(group_vars)
         return data
 
-    def prep(self, data=None, fresh=False):
+    def prep(self, data=None, refit=False):
+        """
+        Fits and transforms, in other words preps, the data.
+        @param data:
+        @param refit: Refit all columns
+        @return:
+        """
         data = self._check_data(data)
         data = copy(data)
-
-        for step in self.steps:
-            data = self._apply_group(data, step)
-            if fresh or not step.trained:
-                data = step.fit_transform(data)
-            else:
-                data = step.transform(data)
-
+        self._apply_fit_transform(self, data, refit)
+        return self
         return pd.DataFrame(data)
-
+        
     def bake(self, data=None):
+        """
+        Transforms, or bakes, the data if it has been prepped.
+        @param data:
+        @return:
+        """
         data = self._check_data(data)
         data = copy(data)
-        
+        self._apply_fit_transform(self, data)
+        return data
+
+    def _apply_fit_transform(self, data=None, refit=False):
+        # applies transform or fit and transform (when refit or not trained yet)
         for step in self.steps:
             data = self._apply_group(data, step)
-            if not step.trained:
-                raise RuntimeError(f'Step {step} not trained. Run prep first.')
+            if refit or not step.trained:
+                data = step.fit_transform(data)
             else:
                 data = step.transform(data)
-
         return pd.DataFrame(data)
 
     def __repr__(self):