Evaluating Drugs for Rare Diseases (DRDs) for the purpose of reimbursement and beyond represents a tremendous challenge for most health care priorities. A consensus is set about the irrelevance of cost e ectiveness analysis to evaluate such drugs. The appeal for multi criteria decision aid models seems reasonable as the evaluation of DRDs is indeed multifaceted. However, the application of MCDA for the purpose of evaluating DRDs is yet primitive and simplistic. The present work tries to tackle the issue of evaluating DRDs from a decision maker angle by adopting an innovative robust ordinal regression MCDA method, UTADIS-GMS, that helps the decision maker discern between the DRDs based on their multi criteria value.