Over the past years, there has been an increasing demand on indoor localization. This has led to diverse solutions: from triangulation algorithms, to the implementation of machine learning technologies. The main difficulty about indoor localization is the precision. In fact, outdoor localization coped the accuracy problem by using the GPS. However, as for indoor location goes, GPS cannot be used because of its low accuracy. Through different implementations, these new technologies and methods have been trying to cope with the problem of accuracy and location prediction in indoor localization. One of the solutions that has been developed, is the use Convolutional Neural Networks (CNNs) by analyzing the Wifi signals of the access points (APs) to predict a location (X,Y).