This paper presents a multi-objective optimization framework for Automated Teller Machine (ATM) placement that balances four key objectives: minimizing travel distance, minimizing financial costs, maximizing user satisfaction, and minimizing environmental footprint. Building on existing facility location research, which has traditionally focused on cost or accessibility, this study advances the state-of-the-art by explicitly incorporating user satisfaction and environmental considerations into the decision-making process. We formulate the ATM placement problem as a multi-objective mixed-integer linear program and employ Monte Carlo simulations (MCS) to simulate varying demand levels, user preferences, and environmental factors. Through Pareto analysis, we identify non-dominated solutions that reveal trade-offs among the competing objectives. For instance, some solutions demonstrate how emphasizing user satisfaction can slightly increase environmental footprint, while others show moderate improvements in travel distance with a negligible impact on operational costs. These findings offer actionable insights for stakeholders, who can select a solution that aligns with their strategic priorities–be it reducing carbon emissions, shortening travel distances, or enhancing user experiences. Overall, our approach not only highlights the inherent trade-offs in ATM network design but also provides a practical roadmap for decision-makers. By illuminating potential gains and losses across multiple objectives, this methodology enables planners to adopt ATM configurations that remain accessible, cost-effective, user-friendly, and sustainable even as demand and environmental conditions evolve.