Groupers are highly susceptible to human-induced impacts, making them one of the most threatened fish families globally. Extinction risk assessments are important in endangered threatened species management, however the most comprehensive—the International Union for Conservation of Nature (IUCN) Red List—cannot classify approximately one-third of grouper species due to data deficiency. We used an ordinal analytical approach to model relationships between species-level traits and extinction risk categories. We found that larger species and those with shallower maximum depths and smaller geographic ranges had higher extinction risk. Using our best fitting model, we classified data deficient grouper species into IUCN's extinction risk categories based on traits. Most of these species were predicted to be of least concern. However, 12% were predicted to be endangered or vulnerable, suggesting that they may be of conservation interest. Importantly, we provide a quantitative method for overcoming data gaps that can be applied to conservation of other species.