Polymer informatics has attracted a great deal of attention due to the amazing progress of artificial intelligence-related technologies in recent years. This chapter reviews the methods of polymer informatics and the current status of the research progress. Starting from the historical backgrounds of artificial intelligence and materials informatics, the procedure of polymer informatics is introduced along with the basic contents of machine learning techniques. We describe the current status of databases useful for polymer informatics and explain methods to represent polymers which have a variety of primary structures and hierarchically constructed higher-order structures. Regarding the databases and polymer representation methods, we describe the difficulties inherent in polymer informatics and discuss recent challenges to solving them. Finally, we describe methods for designing novel polymer materials using deep learning and present recent results including examples of their application to functional polymers.