Mental health challenges are increasingly affecting undergraduate engineering students, who experience elevated stress, burnout, and reduced well-being compared to peers in other disciplines [1]. Despite increased awareness, institutions often struggle to allocate mental health resources in ways that are transparent, equitable, and evidence based. This paper introduces a hybrid decision-making framework that combines the Analytic Hierarchy Process (AHP) and Goal Programming (GP) to guide engineering colleges in making equity-conscious decisions about mental health support services. We simulate the application of this model in a mid-sized engineering college setting, considering five intervention options: counseling expansion, peer-led workshops, culturally responsive wellness programs, digital therapy platforms, and quiet spaces. Stakeholders' decision criteria for weighing options include the impact on equity, accessibility, cost, and scalability. The AHP weighting process assigned the highest importance to equity impact (0.40), followed by accessibility (0.30), while Goal Programming identified four interventions that could be implemented within the institutional budget. Our simulation results prioritize peer-led and culturally responsive interventions over traditional services, suggesting that equitable mental health support in engineering requires reimagining resource allocation. This study contributes a rigorous yet flexible framework for resource planning, aligning institutional values with structural decisions to better serve marginalized student populations.