The structural performance of automotive doors is highly dependent on their metallic support; however, conventional development processes often involve multiple CAD-CAE iterations, which increase lead time and engineering effort. This study presents a methodology for optimizing metallic support geometry by integrating Computer-Aided Design (CAD), Computer-Aided Engineering (CAE), and the Taguchi Design of Experiments (DOE). A Taguchi L16 orthogonal array was used to evaluate eight key geometric factors, including material thickness, fixation point configuration, and geometric reinforcements. Finite element simulations with a meshless solver significantly reduced pre-processing time without compromising accuracy. By analyzing the signal-to-noise (S/N) ratio, the optimal factor combination was identified, which maximized stiffness while minimizing displacement and ensuring robustness against material variability. The optimal design achieved a stiffness of 248 N/mm, a substantial increase over the baseline’s 39 N/mm. This design demonstrates the potential of this methodology to dramatically improve structural performance from the early stages of development and accelerate product development by reducing design iterations.