We have considered Li, Na and K-ion electrode materials and their available battery data from Materials Project database. Suitable features have been considered and developed to train the various machine learning algorithms. The available data has been divided into train set and validation set. The train set has been fitted using various ML algorithms like support vector machine, extratrees regressor and kernel ridge regression to learn the nature of the data and features.