In this work, a computational fluid dynamics (CFD) model was coupled with an advanced statistical strategy combining design of experiments (DoE) and the Monte Carlo method to comparatively optimize and test the robustness of two municipal solid waste (MSW) gasification processes one using air-carbon dioxide (CO2) mixtures as a gasifying agent and the other using air alone. A 3(k) full factorial design of 18 computer simulations was performed using as input factors for air-CO2 mixtures the equivalence ratio and CO2-to-MSW ratio, while MSW feeding rate and air flow rate were used for air gasification. The selected responses were CO2, H-2, CO, and CnHm generation, CH4/H-2 and H-2/CO ratios, carbon conversion, and cold gas efficiency (CGE). Findings were that DoE allowed determining the best-operating conditions to achieve optimal syngas quality. Monte Carlo identified the best-operating conditions reaching a more stable high-quality syngas. Air-CO2 mixture gasification showed enhanced responses with major improvements in CO2 conversion and CGE, both up to a 13% increase. The optimal operating conditions that set the optimized responses showed to not always imply the most stable set of values to operate the system. Finally, this combined optimization process performance revealed to grant professionals the ability to make smarter decisions in an industrial environment.