This article presents a proposal for a tool to combat non-technical losses in electricity distribution systems, based on Machine Learning techniques and consumer data from a Brazilian energy distributor. An exploratory analysis of the data was carried out to identify the variables to be used in training the models, with the purpose of selecting facilities to be inspected on site. The model with the best theoretical result was used on site tests.