Electron beam welding (EBW) is one of the most promising welding methods since it offers excellent strength, precise weld quality, and minimal heat-affected zone (HAZ). EBW is the preferred method for joining Ti-6Al-4V, a highly versatile alloy with applications in the aerospace, automobile, and manufacturing industries. In this study, Ti-6Al-4V alloy butt joints have been carried out through EBW. Statistical analysis and multi-objective metaheuristic techniques have been proposed here for the optimization of EBW parameters. The input parameters considered were the current, accelerating voltage, and scan speed, while the output parameters were the depth of penetration and bead width. Statistical regression analysis was utilized to predict the best possible output parameters. Among the metaheuristic techniques, Multi-objective Bonobo Optimizer (MOBO), Non-dominated Sorting Genetic Algorithm II (NSGA II), and Multi-objective Grey Wolf Optimizer (MOGWO) were applied to achieve multi-objective optimization. Consequently, from the statistical analysis, it was inferred that the current and scan speed were the most influential input parameters for bead width and depth of penetration. Subsequently, among the metaheuristic techniques, NSGA II provided the best Pareto-optimal front, evaluated through the Hypervolume Indicator and Spacing Metric. MOBO gives the next best Pareto-optimal front, followed by MOGWO. Furthermore, Confirmatory tests were performed to experimentally validate the simulated results and the practical outputs closely matched those suggested by the best-performing algorithm (i.e., NSGA II). Finally, it is found that the effective ranges of the input parameters in the Pareto-optimal front are much smaller than the ranges that were experimentally evaluated. This will minimize experimental runs, time, and cost which is useful in future studies. These findings suggest that EBW ensured complete penetration with minimal distortion weld for Ti-6Al-4V alloy.