This study explores the potential of university-community partnerships to enhance sustainability in food systems, focusing on the development of sustainability labels in Chile. The initiative classifies foods into high, medium, and low sustainability categories based on factors such as water footprint, carbon footprint, packaging material, and processing level (using the NOVA classification). The research involved focus groups with experts to define key sustainability dimensions, the construction of a food database, and the calculation of sustainability scores through a Multi-Criteria Decision-Making approach. A predictive classification function was developed using discriminant analysis. Key findings indicate that water and carbon footprints are the most significant factors in determining food sustainability. The predictive model demonstrated a high accuracy rate, correctly classifying 94% of foods. While the study provides a valuable framework for policymakers and stakeholders to promote sustainable food products, its focus on Chile and reliance on the NOVA system may limit the generalizability of its findings. Future research should explore alternative metrics and broader geographic contexts. This research underscores the importance of minimizing environmental impacts and the role of universities in promoting sustainability through collaboration with local communities, offering a practical tool for policy and consumer decision-making.