The objective of this study was to analyze the impact of the use of predictive models in decision-making in the business environment. Using a quasi-experimental design, regression models, decision trees, and neural networks were applied to predict sales, and their effectiveness was compared to decisions made without a model in a sample of 30 retail stores. The results indicate that the use of models, particularly decision trees, significantly improved the accuracy of inventory management predictions and decisions, reducing errors by 20% compared to the control group. It is concluded that predictive models are a useful tool to improve business decision making.
