Health insurance risk analysis is crucial to the development of the insurance industry, allowing insurance companies to anticipate potential losses in health insurance’s inverted product life cycle. The health insurance risk evaluation process is, however, carried out in various ways, which limits the application of transparency, fairness, and justice principles in the calculation of risk rewards. By combining cognitive mapping and measuring attractiveness by a categorical-based evaluation technique (i.e., MACBETH, a multiple-criteria decision analysis technique), this study sought to create a nonparametric and distinctive decision support system for individual private health insurance risk analysis. The proposed system facilitates greater transparency in the calculation of health insurance risk rewards. The results of a real-world application of this system were analyzed and discussed in face-to-face group meetings with independent experts who work for two of the largest insurance companies in Portugal, thereby incorporating realism into the proposed evaluation mechanism. The advantages and limitations of this assessment framework are also discussed.