As the global demand for sustainable fuels increases, bioethanol derived from food waste offers a double solution by producing renewable energy and reducing organic waste. However, food waste that is rich in lipids introduces a hurdle by inhibiting microbial fermentation, leading to reduced ethanol yields. This study seeks to evaluate the kinetic model that captures lipid-induced fermentation inhibition dynamics. A modified Monod–Andrews kinetic expression was employed to simulate microbial growth in the presence of lipids, particularly free fatty acids and triglycerides, to account for the non-linear relationship between substrate concentration and reaction rates. Parameters evaluated included the max specific growth rate (0.-0.5 h^-1 ), substrate concentration (which varied between 5 and 100 g/L), half-saturation constant (1-5 g/L), lipid inhibition constant (1-10 g/L), and lipid content (0-20%), as well as yield coefficient (0,45-0,51 g/g). The Monod–Andrews kinetic expressions were solved with the use of the ODE45s solver in MATLAB to address the kinetics of microbial growth and substrate consumption. A sensitivity analysis was performed on key variables to assess how input variables affect lipids in bioethanol production. Statistical validation metrics such as the root mean square error (RMSE) and coefficient of determination (R²) were used to express the model's prediction accuracy, with an R2 of 0,9842 and an RMSE of 0,4948, showing its strong predictive capability. The results indicate that lipid concentrations above 5–10% (w/w) reduce the ethanol yield by over 25%, with strong inhibition from free fatty acids. Simulated pre-treatment strategies improved the ethanol yield by 15–30%, validating the model's utility. This study delivers a scalable kinetic framework for predicting fermentation outcomes and optimizing bioethanol production systems that are rich in lipids.