Nowadays, performance improvement on ground vehicles is prefominant. This improvement is highly correlated with its control systems. To design its control system, with parts as electronic system for stabilization or anti-rollover control, it is necessary to provide the behavior of the vehicle in certain dynamics conditions. This prediction, of the dynamics behavior of the vehicle, is done by mathematical models that depend directly on its dynamics parameters such as gravity center position, inertia moments, among others. Taking into account the actual background, dynamics parameters of the vehicle have an importante role in the improvement of vehicle s performance, as well as in the optimization of its subsystems. This thesis presentes the vehicle and calibration of the mathematical model developed. For the estimation step, two vehicle models were developed, the first one was done in MATLAB with 4 DOF and the other was treated as a black box, which is obtained by Dynamic-Link Libraries (DLLs) from the free vehicular simulation software. Optimization methods, such as Differential Evolution, Generalized Pattern Search, Mesh Adaptive Pattern Search and Nelder Mead, were used to estimate vehicle s dynamics parameters. The fitness function is defined as a difference between the real response of the vehicle (given by vehicular simulation software) and one calculated with each optimization method. The dynamics parameters estimated with the best optimization method are input for the mathematical model developed in MATLAB to calibrate the model. Finally, the calibrated model is simulated with different maneuvers, this is done to test the robustness of the method and the coherence of estimated parameters.