This paper examines a range of time series forecasting techniques for a casual dining restaurant in Jeddah using
daily sales data. Accurate sales forecasting is essential for restaurants as it directly impacts inventory management,
operational planning, and customer satisfaction. In the food industry, products have a very short shelf life, which
makes balancing supply and demand especially challenging. When forecasts are inaccurate, the restaurant may face
two major issues: food shortages that lead to customer dissatisfaction or overstock that results in increased costs and
food waste.By applying and comparing different forecasting techniques, this study aims to identify the method that provides the
most reliable and practical results. The findings will benefit restaurant managers in planning inventory more
efficiently, reducing waste, improving decision-making, and ultimately enhancing overall business performance.
This research highlights the importance of data-driven strategies in today’s competitive food service industry.