An entropy-based method is presented to model a decision-maker’s (DM’s) subjective utility for a criterion value. The proposed method considers distribution of all the values that the criterion takes for the given set of alternatives. Based on the utility so modeled, and and the DM’s attitudinal character, a multi criteria decision aiding (MCDA) approach is developed to find the best alternative. The proposed method and the approach are applied in a real car selection case-study.