Multiple-Criteria Decision Aid (MCDA) has long been considered in a single decision-making framework. Nowadays, the need to take into account several contradictory opinions handled by several decision-makers arises. Thus, researchers are interested in multi-criteria problems involving several decision-makers. In this context, to solve the classification problem, we propose an aggregation model based on the geometric mean and the comparison score on the considered criteria. Comparisons with two methods, AHP and TOPSIS, are performed on numerical data. It is clear that the proposed aggregation function is better depending on the complexity of the calculation and the computation time. Further research in this field is proposed.