Fuzzy logic has emerged as a transformative tool in nutrition science, providing innovative solutions to address the inherent complexity and variability of dietary planning and nutritional assessment. This paper explores the application of fuzzy logic in nutrition, highlighting its ability to manage ambiguity, process vague data, and provide adaptive dietary recommendations tailored to individual and population needs. Key applications include personalized nutrition, clinical dietary management, and public health strategies. The integration of fuzzy logic with advanced computational tools has the potential to revolutionize how nutrition-related decisions are made, contributing to improved health outcomes and dietary sustainability.