An ever-growing catalog of human variants is hosted in the ClinVar database. In this database, submissions on a variant are combined into a multisubmitter record; and in the case of discordance in variant classification between submitters, the record is labeled as conflicting. The current study used ClinVar data to identify characteristics that would make variants more likely to be associated with the conflict class of variants. Furthermore, the Extreme Gradient Boosting algorithm was used to train classifier models to provide prediction of classification discordance for single submission variants in ClinVar database.