Call the model.predict_proba() method with the argument X_test to use the fitted model to predict values for the test data. Store the outcome in the variable probability_predictions. Note that the predict_proba() method returns two columns, one column per class label. The first column contains the probability that an unlabeled example belongs to class False (Churn is "False") and the second column contains the probability that an unlabeled example belongs to class True (Churn is "True")