diff --git a/MaCh3PythonUtils/machine_learning/fml_interface.py b/MaCh3PythonUtils/machine_learning/fml_interface.py
index 86d99bc..6a22cd6 100644
--- a/MaCh3PythonUtils/machine_learning/fml_interface.py
+++ b/MaCh3PythonUtils/machine_learning/fml_interface.py
@@ -7,6 +7,7 @@
 from matplotlib.colors import LinearSegmentedColormap
 
 from sklearn import metrics
+from sklearn.preprocessing import StandardScaler
 import matplotlib.pyplot as plt
 import scipy.stats as stats
 import numpy as np
@@ -40,6 +41,7 @@ def __init__(self, chain: ChainHandler, prediction_variable: str) -> None:
         self._training_labels=None
         self._test_data=None
         self._test_labels=None
+        self._scalar = StandardScaler()
             
     def __separate_dataframe(self)->Tuple[pd.DataFrame, pd.DataFrame]:
         # Separates dataframe into features + labels
@@ -52,6 +54,8 @@ def set_training_test_set(self, test_size: float):
         # Splits in traing + test_spit
         features, labels = self.__separate_dataframe()
         self._training_data, self._test_data, self._training_labels, self._test_labels =  train_test_split(features, labels, test_size=test_size)
+        self._training_data = self._scalar.fit_transform(self._training_data)
+
 
     @property
     def model(self)->Any:
diff --git a/MaCh3PythonUtils/machine_learning/scikit_interface.py b/MaCh3PythonUtils/machine_learning/scikit_interface.py
index 719f65e..3564bcb 100644
--- a/MaCh3PythonUtils/machine_learning/scikit_interface.py
+++ b/MaCh3PythonUtils/machine_learning/scikit_interface.py
@@ -26,8 +26,11 @@ def train_model(self):
         self._model.fit(self._training_data, self._training_labels)
         
     def model_predict(self, test_data: DataFrame):
+        
+        scale_data = self._scalar.transform(test_data)
+        
         if self._model is None:
             raise ValueError("No Model has been set!")
 
-        return self._model.predict(test_data)
+        return self._model.predict(scale_data)
     
\ No newline at end of file
diff --git a/MaCh3PythonUtils/machine_learning/tf_interface.py b/MaCh3PythonUtils/machine_learning/tf_interface.py
index c61bd67..2f5c4c5 100644
--- a/MaCh3PythonUtils/machine_learning/tf_interface.py
+++ b/MaCh3PythonUtils/machine_learning/tf_interface.py
@@ -48,6 +48,9 @@ def save_model(self, output_file: str):
     def load_model(self, input_file: str):
         self._model = tf.saved_model.load(input_file)
     
-    def model_predict(self, testing_data):
+    def model_predict(self, test_data):
+        
+        scale_data = self._scalar.transform(test_data)
+
         # Hacky but means it's consistent with sci-kit interface
-        return self._model.predict_on_batch(testing_data).T[0]
+        return self._model.predict_on_batch(scale_data).T[0]
diff --git a/configs/tensorflow_config.yml b/configs/tensorflow_config.yml
index 7fbc6c3..9d2d0f2 100644
--- a/configs/tensorflow_config.yml
+++ b/configs/tensorflow_config.yml
@@ -15,7 +15,7 @@ FitterSettings:
 
     FitterPackage : "TensorFlow"
     FitterName : "Sequential"
-    TestSize : 0.9
+    TestSize : 0.4
 
     FitterKwargs:
         BuildSettings:
@@ -25,15 +25,18 @@ FitterSettings:
         Layers:
             - dense:
                 units: 128
+                activation: 'relu'
             - dense:
                 units: 64
+                activation: 'relu'
             - dropout:
                 rate: 0.5
             - dense: 
                 units: 16
+                activation: 'relu'
             - dense:
                 units: 1
 
         FitSettings:
             batch_size: 100
-            epochs: 10
\ No newline at end of file
+            epochs: 200
\ No newline at end of file