This paper proposes a hybrid algorithm based on the demand-driven manufacturing resources planning (DDMRP) model and machine learning techniques to determine when and how much to purchase a product. The DDMRP model optimises the inventory using predictive models to determine the product demands, and the behaviour of the providers. Then, our DDMRP model determines when and how much to purchase. Thus, our approach defines a smart inventory management to establish what should be purchased and when. The preliminary results are very encouraging because the inventory follows the optimal levels by product based on demand, avoiding a lack of inventory.