 A new approach for the multi group classification problems  Using the regression analysis for the obtaining the classification scores  Using the mathematical programming for the classifying of the units Classification is the problem of identifying to which of a set of categories a new observation belongs, on the basis of a training set of data containing observations whose category membership is known. In this study, for solving multi-group classification problems, a new two-stage hybrid classification method based on regression analysis and mathematical programming has been developed. In the first step of the proposed method, the classification score of each unit is estimated with the help of the linear regression equation for each unit. In the second step, the classification of the units is performed by the mathematical programming model based on clustering analysis. Figure A. Flow chart of proposed method Purpose: In this study, for solving multi-group classification problems, a new method has been proposed based on regression analysis and mathematical programming classification method. The purpose of this study is handled the multi-group classification problem with the help of the superiority of regression analysis from the statistical theory and the flexibility of mathematical programming by a two-stage detailed examination idea. Theory and Methods: The proposed method combines the strengths of regression analysis and mathematical programming method. Results: From the 10 real data sets taken the well-known literature and simulation study results, it is observed that the proposed method outperforms the regression analysis, mathematical programming and artificial neural network based classification methods. Conclusion:With the proposed method, it is possible to achieve high correct classification success in the multiclass classification problems.