A common problem faced by companies is predicting future production of goods based on previously recorded data. The company produces only according to orders, conducting production processes solely based on consumer demand. Any excess production is stored as stock to meet sudden consumer demands. These predictions significantly influence management decisions regarding the quantity of goods that must be prepared, considering factors like general business and economic conditions, competitors' actions, government policies, market trends, product life cycles, styles and fashions, changes in consumer demand, and technological innovations. This research aims to identify and analyze screen printing production predictions using the Moving Average and Exponential Smoothing methods. The more data used for comparison, the more accurate the prediction results. The research successfully developed a screen printing production prediction system, facilitating easier determination of future production quantities.