Demand forecasting is the process of predicting what the demand for certain products will be in the future. This helps manufacturers to decide what they should produce and guides retailers toward what they should stock. Demand forecasting is aimed at improving, for example, the following processes: • Supplier relationship management. • Customer relationship management. • Order fulfillment and logistics. • Marketing campaigns. • Manufacturing flow management. Through Machine Learning techniques we can predict the amount of products/services to be purchased during a defined future period. In this case, the system using Machine Learning can learn from the data for improved analysis. Compared to traditional demand forecasting methods, a Machine Learning approach allows you to: • Accelerate data processing speed • Provide a more accurate forecast • Automate forecast updates based on recent data • Analyze more data • Identify hidden patterns in the data • Create a robust system • Increase adaptability to change In this presentation, we will see how to apply Machine Learning techniques, like Neural Network on Demand Forecast to obtain better results and how to use them in different contexts.