This study presents a novel fuzzy logic-based methodology for educational assessment, utilizing the Matlab Fuzzy toolbox to integrate diverse stakeholder perspectives. The model incorporates four distinct input variables: Managers’ responses (MR), Academic staff members’ responses (ASR), Students’ responses (SR), and Alumni responses (AR). Through carefully defined membership functions for each input variable, the research establishes a systematic framework to address the inherent uncertainties in educational evaluation. The methodology employs a rule-based inference system with multiple conditional statements that assign different weights to stakeholder feedback, thereby creating a nuanced output scale ranging from “very low” to “very high.” This approach enables comprehensive analysis of educational quality by balancing the sometimes conflicting perspectives of different stakeholders. The model’s efficacy is demonstrated through rule viewers and surface viewers that visualize the complex relationships between inputs and outputs, offering an intuitive understanding of the system’s behavior under various scenarios. This fuzzy logic framework provides educational institutions with a robust tool for decision-making that acknowledges the complexity and subjectivity inherent in educational assessment processes.