A new approach is presented to optimize the tool life of solid carbide end mill in high-speed milling of 7050-T7451 aeronautical aluminum alloy. In view of this, the multi-linear regression model for tool life has been developed in terms of cutting speed and feed per tooth by means of central composite design of experiment and least-square techniques. Variance analyses were applied to check the adequacy of the predictive model and the significances of the independent parameters. Response contours of tool life and metal removal rates were generated by using response surface methodology (RSM). The analysis results show that it is possible to select an optimum combination of cutting speed and feed per tooth that improves metal removal rate without any sacrifice in tool life.