In recent years the science of studying the movement of people indoors has grown rapidly.This study primarily helps ensure the safety of citizens, facilitates them, and provides information and entertainment to those who desire it.To accomplish this, the user must first have their consent and actively participate through their mobile device in order to be able to be identified by specific machines and technologies installed for this purpose.One challenge of this research field is to predict the location of the individual either at the next moment or at some point in the future, which provides various benefits for both himself and the owners of the shops and companies as it allows, among other things, targeted advertising and services supply directly to the user depending on their location.The present thesis mainly applies machine learning algorithms but also deep learning algorithms on given open data of a shopping mall to predict the next location within the space.The purpose is to compare the results they produce, study and analyze the accuracy of the prediction and ultimately determine their suitability under specific conditions and parameters.To do this, both past visited locations and demographic characteristics of the citizens were used.