Automobile companies that spend billions of dollars annually towards warranty cost, give high priority to warranty reduction programs. Forecasting of automobile warranty performance plays an important role towards these efforts. The forecasting process involves prediction of not only the specific months-in-service (MIS) warranty performance at certain future time, but also at future MIS values. However, maturing data (also called warranty growth) phenomena that causes warranty performance at specific MIS values to change with time, makes such a forecasting task challenging.Although warranty forecasting methods such as log-log plots and dynamic linear models appear in this paper we use an artificial neural network for the forecasting of warranty performance in presence testing errors using response surface methodology. This application shows the effectiveness of neural phenomena.