diff --git a/BayesValidRox/surrogate_models/surrogate_models.py b/BayesValidRox/surrogate_models/surrogate_models.py
index dbfee1347000ff0df4657b5f43819edbd927a1ba..a9d8391c031748e3cf2cb8e849b17e2e1f784ad6 100644
--- a/BayesValidRox/surrogate_models/surrogate_models.py
+++ b/BayesValidRox/surrogate_models/surrogate_models.py
@@ -784,7 +784,8 @@ class Metamodel:
         self.gp_poly = self.AutoVivification()
         self.pca = self.AutoVivification()
         self.LCerror = self.AutoVivification()
-            
+        self.x_scaler = {}
+
         if self.ExpDesignFlag != 'sequential':
             # Read observations or MCReference
             if Model.MeasurementFile is not None or len(Model.Observations) != 0:
@@ -839,8 +840,14 @@ class Metamodel:
                 
             # Parallel fit regression
             if self.metaModel.lower() == 'gpe':
+                # Prepare the input matrix
+                scaler = MinMaxScaler()
+                X_S = scaler.fit_transform(CollocationPoints)
+                
+                self.x_scaler[key] = scaler
+                
                 outDict = Parallel(n_jobs=-1, prefer='threads')(
-                    delayed(self.GaussianProcessEmulator)(CollocationPoints,OutputMatrix[:,idx]) 
+                    delayed(self.GaussianProcessEmulator)(X_S,OutputMatrix[:,idx]) 
                             for idx in range(OutputMatrix.shape[1]))
                 for idx in range(OutputMatrix.shape[1]):
                     self.gp_poly[key]["y_"+str(idx+1)] = outDict[idx]
@@ -1941,8 +1948,9 @@ class Metamodel:
                 
                 # Perdiction with GPE
                 if self.metaModel.lower() == 'gpe':
+                    X_T = self.x_scaler[Outkey].transform(samples)
                     gp = self.gp_poly[Outkey][Inkey]
-                    y_mean, y_std = gp.predict(samples, return_std=True)
+                    y_mean, y_std = gp.predict(X_T, return_std=True)
 
                 else: # Perdiction with PCE or pcekriging
                     # Assemble Psi matrix