Advanced analytics and machine learning algorithms for predictive maintenance on Medium Voltage (MV) distribution network The world of the energy production is quickly changing thanks to the advent of renewable sources of energy and the birth of new entities in the energy production chain like the prosumers. This is making the Distribution System Operator (DSO) more focused on what concerns the data they get from the distribution network in order to improve the system management. In this optics, the work of the thesis focuses on the analysis of SCADA events regarding Medium Voltage lines recorded from 2010 to 2016 in order to apply predictive maintenance.