(untitled) (International Journal of Food and Nutritional Sciences, 2026)
Career guidance often involves analyzing uncertain, imprecise, and subjective information such as student preferences, aptitudes, skills and academic performance. Traditional fuzzy or intuitionistic fuzzy models handle some of this uncertainty, but fall short when Multi dimensional vagueness exists. This paper introduces a novel distance-based framework using Multi vague sets, which can represent multiple levels of truth, falsity and hesitation for each attribute. We apply this model to career counseling by comparing a students Multi vague profile with those of various career options. The proposed system computes distance measures between student profiles and ideal job requirement profiles to recommend the most suitable career paths. Experimental results validate the approach, demonstrating its effectiveness in handling uncertainty and improving the decision-making process in career guidance.