Hydrogen can be the fuel of the future, and there are multiple approaches for its production and storage. Most hydrogen production comes from non-renewable sources, primarily natural gas reforming, which is efficient but unsustainable. Microbial electrolysis cells (MEC) are alternative developing technologies that exploit conductor-like properties of electrogenic bacteria to both oxidize organic contaminants and get protons reduced in a cathode, thus producing hydrogen. Here, the aim is to design a model-based optimization framework to intensify the MEC efficiency. The constructed process model is proposed by considering transport phenomena, microbial kinetics, and a secondary current distribution model to estimate steady-state reactor performance and electrical efficiency. The results show a value of 25 % for electrical efficiency as hydrogen recovered. Global sensitivity analysis was performed and determined a strong dependency on inlet liquid velocity, and a built-in, gradient-free optimization algorithm was implemented to the model to maximize electrical efficiency under a defined range of inlet liquid velocity, inlet substrate concentration, and applied voltage. The proposed model predicts a maximum increase of efficiency of about 267 % by increasing inlet velocity and substrate concentration. Intensification of the cell's performance can be greatly achieved when halving hydraulic retention time and by having a more concentrated feed.