customer_features = ['credit_score', 'balance', 'total_purchases', 'last_active']

historical_features_df = feast.get_historical_features(customer_ids, customer_features)
model = ml.fit(historical_features_df)  # pseudo code

online_features = feast.get_online_features(customer_ids, customer_features)
prediction = model.predict(online_features)