The goal of the current research was to study the behavior of the fermentation process of home-made beer using a mathematical dynamic model. The model contains the rates of change of the concentration state variables of glucose, maltose and maltotriose. An output variable is the ethanol concentration and an auxiliary variable is the biomass (yeast) concentration. The model was programmed in the Matlab-Simulink environment, and for its numerical integration Dormand-Prince method of fourth order with a variable integration step size and a relative tolerance of 10−8 was used. In order to know which model parameters are more important, a local sensitivity analysis was carried out. Furthermore, an experiment was performed to produce home-made beer at constant temperature (21°C). Fourteen experimental units (fermenters) with the same initial conditions were implemented. Using the experimental results the model was calibrated by nonlinear least squares and differential evolution algorithms. According to the statistics bias (BIAS), correlation coefficient (r), squared root of mean squared error (RMSE), mean absolute error (MAE) and the efficiency of modeling (EF), a good fit between the model predictions and measurements were found after the model parameters estimation.