In dentistry, endodontics is the study of dental pulp and tissues surrounding the roots. Endodontic treatment is otherwise called root canal treatment. The importance of endodontics focuses on several therapies to protect human teeth from cavities or infections, injuries, and various oral diseases like oral cancer and periodontal disease. Over 3.5 billion people are affected by various oral diseases, 10% of the global population is affected by periodontal diseases, and 530 million children suffer from tooth decay. There are different types of root canal morphology and configurations in which multiple abnormalities exist, such as C-shaped canals, fusion of roots, dens invaginatus, distolingual root, taurodontism, root dilaceration, etc. AI plays a vital role in endodontic applications. Using AI for the prediction and diagnosis of periapical lesions, root fractures can be detected. Nowadays, AI is used to determine working length measurements, predict dental pulp stem cells, and guide retreatment procedures. Therefore, AI provides successful outcomes and improvements in diagnosis and prediction in root canal applications in day-to-day practices. This review chapter summarizes different deep learning techniques that can be implemented in various endodontic applications in detail to understand the pros and cons.