This study investigates the multi-objective optimization of a two-stage helical gearbox using the Multi-Objective Evolutionary Algorithm based on Decomposition with Differential Evolution (MOEA/D-DE). The design problem involves two conflicting objectives: minimizing the gearbox bottom area to achieve a compact structure, and maximizing the gearbox’s mechanical efficiency. A detailed mathematical model is developed, incorporating geometric, kinematic, and operational constraints relevant to industrial gearbox applications. MOEA/D-DE is adopted as the primary optimization technique due to its robustness in handling complex, non-linear design spaces and its ability to maintain a well-distributed Pareto front. The algorithm effectively captures the trade-offs between compactness and efficiency, offering diverse optimal design solutions for engineering decision-making. Results confirm that MOEA/D-DE is a powerful and reliable method for solving real-world gearbox design problems with multiple performance goals.