In this thesis we consider the electricity consumption of a chemical plant located in Chiayi area, and the objective is to establish forecasting models for the plant’s electricity consumption. First, we collect the monthly electricity consumption data of the plant, ranging from 2010 to 2013. Then, we establish two forecasting models by applying both regression analysis and seasonal pattern analysis on the collected data. Finally, we use both models to predict the plant’s monthly electricity consumption for 2014, and the predicted result are compared with the actual monthly electricity consumption data. The results show that the predicted accuracy of both models are quite promising, and can provide useful information for the planning of future power budget and equipment revamping of the chemical plant.