Over the past years, the engine emission regulation has become of crucial importance and the development of Hybrid Electric Vehicles (HEV) is one of the best solutions in the market. Besides the emissions reduction, this class of vehicles has to satisfy important performances constraints. For this reason, the aim of this project is to develop a new algorithm capable of classifying the admissibility of hybrid electric vehicle layouts, which means to check if the performance index of each layout is lower than a predefined threshold. This algorithm exploits Deep Neural Network (DNNs), an artificial neural network (ANN) with multiple layers between the input and output layers.