Lately the level of competition between companies in the light automotive industry is reaching a very high level, due to the various strategies developed by many competitors. Our study seeks to strengthen the evaluation of forecasts to improve the organization's capability to anticipate future events in important business processes, such as sales and maintenance services. To achieve this objective, investigations related to Data Mining techniques were consulted, in order to perform an information analysis with a predictive approach. Our research involves designing different models applying methods such as regressions, neural networks and decision trees, to a historical database of an automotive organization, previously selecting data using techniques such as the correlation matrix and PCA (Principal Component Analysis). Finally, an evaluation is carried out on the results obtained after ...