The use of Artificial Intelligence with the help of machine learning has eased the work of healthcare practitioners. This systematic review aims to find effective machine learning models to detect dental caries and oral cancer. Image datasets used in the studies ranged from 74 to 3000 images. Different researchers used different approaches and different evaluation metrics to evaluate their studies with Accuracy and Area Under the Curve (AUC) being the most common metrics. The current implementations of machine learning models lay a foundation to reduce the time and effort required to develop newer models for future developments. Overcoming limitations of small datasets, data integration, and dataset standardization will increase the performance and accuracy of the models and will help machine learning become an integral part of dentistry. © 2022 IEEE.