Any organization engaged in trading aims to maximize earnings while maintaining costs at their bare minimum. One of the inexpensive ways to accomplish this objective is through sales forecasting. Evidence from empirical literature has shown that sales forecasting frequently results in better customer service, fewer returns of goods, less dead stock, and effective production scheduling. Successful sales forecasting systems are essential for the food sector because of the limited shelf life of food goods and the significance of product quality. In this paper, we generated sales of forecasts for a perishable dairy drink using the famous ARIMA approach. We identified the ARIMA (0, 1, 1)(0, 1, 1)12 as the proper model for modeling the daily sales forecast of the perishable drink. After performing model diagnostics, the model satisfied all the model assumptions, and a strong positive linear relationship (R2 > 0.9) was observed when the actual daily sales were regressed against the forecasted values.