Electricity plays a vital role in this modern world. It is considered the backbone of an economy's prosperity and progress. The availability of a huge amount of energy has resulted in a shorter working day, higher agricultural and industrial production, and have better transportation facilities. Modern society is so much dependent upon the use of electrical energy that it has become part of our life. It forms a key part of human everyday life. As the economy grows, demand for energy increases. Cagayan de Oro City's growing population and developing technology have demanded increasing consumption of electrical energy to provide light, heat, and power for the countless machines that are essential to the life and work of the residents. Usage will continue to increase because of rising living standards but higher costs may act to reduce the rate of rising. With the premise, there is a need to predict the future electrical power consumption to help CEPALCO to be prepared and for them to provide sufficient electrical energy for Cagayan de Oro City. Statistical forecasting is a method that uses the past to predict the future by identifying trends and patterns within the data to develop a forecast. The study deals with the application of autoregressive integrated moving average (ARIMA) for electrical power consumption in Cagayan de Oro City. After obtaining the results of ARIMA, it shows that ARIMA accumulates less absolute percentage error. The reason why ARIMA performed well is that the nature or behavior of the data that have been gathered contains linear trends although the data are fluctuating still the behavior is increasing which implies that the data of the monthly electricity consumption are more likely linear. Hence, the more the behavior of the data becomes linear, the more ARIMA is effective in forecasting.