The most important challenges in electric load forecasting is to find the accurate electricity load forecasting. Because, it is volatile in nature and has to be consumed immediately. Fuzzy Decision Tree is applied to predict the annual electricity requirement in India. Population and Per Capital gross domestic product (GDP) are taken as input variables and the electricity consumption is predicted output variable. Past 30 years of historical data has been used for training and 4 year of data is used for testing the fuzzy decision Tree. Comparatively to measure the accuracy of data has been made with Artificial Neural Network and Fuzzy Decision Tree model using Mean Absolute percentage error (MAPE). The results states that proposed Decision Tree model has given high performance and less error rate than the Artificial Neural Network model.