A new approach for the prediction of lift, drag and moment coefficients is presented. This approach is based on the Support Vector Machines methodology, and on a optimization algorithm, the Extended Great Deluge. The novelty of this approach is the combination between the SVM and the EGD algorithm. The EGD is used to optimize the SVM parameters to allow it to predict the aerodynamic coefficients of ATR 42 model.The training and validation of this new combination method is realized using the aerodynamic coefficients of an ATR-42 wing model with Xfoil software and experimental tests using the Price-Païdoussis wind tunnel. The results obtained with our approach are compared with the XFoil results, experimental results and XFLR5 software results for different flight cases, expressed as various combinations of angles of attack and Mach numbers. The main purpose of this methodology is to rapidly predict aircraft aerodynamic coefficients.