Scholarship selection in higher education requires a transparent procedure because candidates are evaluated through criteria with different levels of importance. This study develops a decision support model that integrates the Best–Worst Method (BWM) for criterion weighting and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) for candidate ranking. The data comprise nine anonymized scholarship candidates evaluated using academic achievement, cumulative grade point average (GPA), and administrative completeness. In the BWM model, GPA was designated as the best criterion and administrative completeness as the worst criterion. The resulting weights were 0.2308 for academic achievement, 0.6923 for GPA, and 0.0769 for administrative completeness, with a fully consistent comparison structure. MOORA calculations were performed using the candidates’ original GPA values rather than converting them into ordinal categories. The results placed alternative A5 first with an optimization value of 0.3509, followed by A2 with 0.3464 and A6 with 0.3426. Because all candidates satisfied the administrative requirement, this criterion contributed the same value to every alternative and did not change the ranking. Sensitivity analysis showed that the top three alternatives remained stable under moderate changes in the relative weights of achievement and GPA, but the ranking changed when GPA became strongly dominant. The model provides a reproducible basis for scholarship decisions while highlighting the need to use administrative completeness as an eligibility filter and to expand substantive assessment criteria in future implementation.