Chargeback fraud is a massive problem for e-commerce businesses. Using historical ticket order data, several machine learning models are trained and tested to predict which transactions are high risk for chargeback. The results of this thesis show that many fraudulent transactions can be successfully identified and stopped before they are processed. Using these types of models could significantly reduce chargebacks, saving companies time and money.