Course scheduling in higher education requires balancing the diverse preferences of students, instructors, and administrators under various logistical constraints. To address the inherent uncertainty in these preferences, this study proposes a fuzzy multi-criteria decision-making (MCDM) framework incorporating four methods: Fuzzy Analytic Hierarchy Process (FAHP), Best-Worst Method (BWM), Fuzzy TOPSIS, and Fuzzy Ordered Weighted Averaging (Fuzzy OWA). A case study involving evaluations from all stakeholder groups is conducted to assess scheduling alternatives based on criteria such as session timing, instructor preferences, classroom suitability, and fairness. The results reveal consistent rankings across methods, with each technique offering unique interpretive advantages–hierarchical structuring (FAHP), simplicity (BWM), intuitive ranking (TOPSIS), and attitudinal flexibility (OWA). This research highlights the potential of fuzzy MCDM approaches to support equitable and robust scheduling decisions under uncertainty.