We developed a sophisticated machine learning algorithm that analyzes each store's historical sales data to predict future sales accurately. Using these predictions, we implemented an optimization algorithm to determine optimal inventory levels for each store. This approach allowed us to align inventory orders and food preparation with actual demand, significantly reducing waste and saving substantial costs in the food industry.