The Box-Jenkins method or the Autoregressive integrated moving average model is a famous technique for forecasting time series data. The study aims to analyze the historical data and develop an appropriate model that will forecast the electricity demand in Davao del Sur province in the Philippines. The dataset used in the paper was provided by the Davao del Sur Electric Cooperative, Inc. (DASURECO, Inc.) upon request through the electronic Freedom of Information (eFOI) website. The annual data cover the years 2000 to 2021. The data series was transformed using the Box-Cox transformation, and differencing was performed to address nonstationarity and nonconstant variance. The best model was selected among the tentative models by selecting the model with the least Akaike Information Criterion (AIC) value. The chosen model has undergone diagnostic checking and found that the residuals behave like white noise. The results show that ARIMA (0,1,0) with drift is the statistically valid model and is suitable for predicting electricity demand. The forecast shows that the electricity demand in the region will continue to increase, and it is predicted that by 2026, the demand will reach 505,246.4 megawatt-hours.