<p>The increasing demand for sustainability, waste reduction, and logistical efficiency has brought renewed attention to reverse logistics in perishable food supply chains. However, supplier selection in this context remains a complex and underexplored problem, particularly due to perishability, quality degradation risks, and operational constraints associated with cold-chain environments. To address this gap, this study proposes a structured decision-support framework tailored to the specific demands of sustainable supplier evaluation in reverse cold chains for perishable goods. This study develops a hybrid multi-criteria decision-making framework that integrates Trapezoidal Fuzzy SWARA and Trapezoidal Fuzzy COPRAS for sustainable supplier selection under uncertainty. The framework evaluates five decision criteria derived through expert consultation and assesses five supplier alternatives within a reverse cold-chain context. TF-SWARA is applied to compute fuzzy criterion weights, while TF-COPRAS determines the relative performance of suppliers based on aggregated fuzzy utility scores. The results show that Supplier A1 achieves the highest utility value, reflecting superior performance in quality assurance, responsiveness, and cost-effectiveness. The proposed framework offers both methodological and practical contributions: it operationalizes supplier evaluation under uncertainty in perishable reverse logistics. It supports managers in making transparent, criteria-driven, and context-sensitive sourcing decisions.</p>