Machine learning techniques have been an important support for disease prediction and diagnosis utilizing genetic variants classification. This scoping review aimed to synthetize the application of machine learning techniques in processing of genetic variants to support clinical diagnosis. Scopus, Web of Science and PubMed databases were used for retrieving the studies to be included in this scoping review. A total of 522 records were retrieved and after the selection process 11 studies were included. Several machine learning techniques have been applied to processing genetic variants related to rare genetic diseases, cancer, autism spectrum disorder and hereditary hearing loss. However, there is no evidence of the translation of these machine learning techniques to the clinical practice.