Facial expressions have a universal communicative value and are naturally recognized by human eye. There are several application’s sectors, spanning from welfare and security fields to neuromarketing, having the purpose to obtain an automatic process of Facial Emotion Recognition (FER) through human expression analysis. In this dissertation it’s analysed this ability, conveyed to an Artificial Intelligence, in order to find its accuracy. Indeed, the capability to acquire the automatic FER comes from Machine Learning, a method through which an algorithm is educated with the aim of gaining experience. Once this training process is finished, the Convolutional Neural Network (CNN) becomes expert and ready to be applied to general cases.