<p>This research presents a benchmark-oriented multi-criterion decision-making (MCDM) framework developed to address the persistent issue of rank reversal in comparative evaluations. By standardizing each criterion using fixed benchmark values and translating performance scores onto a uniform 0–100 scale, the method ensures that rankings remain consistent, regardless of changes in the set of alternatives. A weighted aggregation mechanism then combines these normalized scores to derive final rankings. The approach is applied to the selection of Cloud Service Providers (CSPs), a critical decision in IT infrastructure planning, and is equally applicable to vendor evaluation and public procurement scenarios where decision stability is crucial. Compared with traditional methods such as TOPSIS, the benchmark-based framework demonstrates superior resilience against rank instability. Through sequential addition/removal tests and sensitivity analysis, the methodology exhibits strong robustness and adaptability to shifting decision priorities. The principal advantage of this approach lies in its independence from the composition of alternatives, which makes it especially valuable in dynamic environments where options evolve over time. Overall, the study delivers a transparent, consistent, and computationally efficient tool for structured decision-making in complex, real-world applications.</p>