Significant research endeavors have focused on microbial fuel cell (MFC) systems within wastewater treatment protocols owing to their unique capacity to convert chemical energy from waste into electricity while maintaining minimal nutrient concentrations in the effluent. While prior studies predominantly relied on empirical investigations, there remains a need to explore modeling and simulation approaches. Assessing MFC systems’ performance and power generation based on real wastewater data is pivotal for their practical implementation. To address this, a MATLAB model is developed to elucidate how MFC parameters and constraints influence system performance and enhance wastewater treatment efficiency. Leveraging actual wastewater data from a municipal plant in Guelph, Canada, six sets of MFC models are employed to examine the relationship between power generation and six distinct parameters (inflow velocity, membrane thickness, internal resistance, anode surface area, feed concentration, and hydraulic retention time). Based on these analyses, the final model projects a total power generation of 50,515.16 kW for the entire wastewater treatment plant in a day, capable of supporting approximately 2530 one-person households. Furthermore, the model demonstrates a notably higher chemical oxygen demand (COD) removal rate (75%) compared to the Guelph WWTP. This comprehensive model serves as a valuable tool for future simulations in similar wastewater treatment plants, providing insights for optimizing performance and aiding in practical applications.