This Master's thesis spans a wide range of fields. Starting from the control domain, a comprehensive review of Model Predictive Control (MPC) was conducted. Subsequently, more emphasis was placed on automotive applications, studying the main kinematic and dynamic models of a vehicle as outlined in Rajamani's texts. The focus then shifted to lateral models, forming the foundation for the subsequent MPC development. The initial phase concluded with an extensive literature review on artificial neural networks (ANNs) and their primary applications, aiming to identify the most suitable one for my work. The thesis's objective is to experimentally demonstrate how computational limitations in the automatic control domain can be easily overcome through the use of simple machine learning techniques.