Medical education is only beginning to explore the factors that contribute to equitable assessment in clinical settings. Increasing knowledge about equitable assessment ensures a quality medical education experience that produces an excellent, diverse physician workforce equipped to address the health care disparities facing patients and communities. Through the lens of the Anti-Deficit Achievement framework, the authors aimed to obtain evidence for a model for equitable assessment in clinical training. A discrete choice experiment approach was used which included an instrument with 6 attributes each at 2 levels to reveal learner preferences for the inclusion of each attribute in equitable assessment. Self-identified underrepresented in medicine (UIM) and not underrepresented in medicine (non-UIM) (N = 306) fourth-year medical students and senior residents in medicine, pediatrics, and surgery at 9 institutions across the United States completed the instrument. A mixed-effects logit model was used to determine attributes learners valued most. Participants valued the inclusion of all assessment attributes provided except for peer comparison. The most valued attribute of an equitable assessment was how learner identity, background, and trajectory were appreciated by clinical supervisors. The next most valued attributes were assessment of growth, supervisor bias training, narrative assessments, and assessment of learner's patient care, with participants willing to trade off any of the attributes to get several others. There were no significant differences in value placed on assessment attributes between UIM and non-UIM learners. Residents valued clinical supervisors valuing learner identity, background, and trajectory and clinical supervisor bias training more so than medical students. This study offers support for the components of an antideficit-focused model for equity in assessment and informs efforts to promote UIM learner success and guide equity, diversity, and inclusion initiatives in medical education.