This paper assesses the predictive accuracy of various analytical models and one numerical model (a CART-ANFIS network) of springback that are available with the existing literature using the mean square error and its decomposition into systematic and random components as a comparative measure of predictive accuracy. The numerical model was found to have no systematic bias in the springback predictions made, whilst for the analytical models the systematic bias accounted for about 11% of the mean square error. The CART-ANFIS network also had the smallest MSE and the prediction errors made were all random in nature. The paper ends by giving some illustrations of the CART-ANFIS numerical model in finding the proper die contour to correct for springback so as to achieve right first-time manufacturing for a wide range of sheet steels.