This study presents the simulation of a MFC with Pseudomonas aeruginosa based on a metabolic flux analysis (MFA) which arises as a linear programming model that served as input for the fuel cell model. The linear model was implemented in Xpress MP? and the coupling model in Comsol Multiphysics?. The in silico model predicted maximum potentials of 0.135 V which were consistent with those obtained in the experimental cell. Afterwards, an optimization platform based on multiobjective optimization approach was implemented aimed to determine genes that increase the average cell power. cysA, cysP and rpoS mutants which were predicted to increase the power of the cell, were experimentally tested with an air cathode fuel cell finding an augment up to 35-fold in the average power density for the rpoS mutant. Power densities were obtained through experimentation in the range of [0.13 - 5] mW/m2. Electron shuttle rise was qualitative corroborated trough cyclic voltammetry tests, which allowed to visualize the augment of the peaks for rpoS mutation.