METHODS-Separately for women and men, we developed three predictive models using unconditional multiple logistic regression for survey data. To account for racial/ethnic disparity in prevalence, initial models included identical predictor characteristics plus information on 1) respondent's race/ethnicity; or 2) respondent's most recent partner's race/ethnicity; or 3) no information on race/ethnicity. RESULTS-C. trachomatis diagnosis was available for 10,928 (88.6%) of the sexually experienced respondents. A combination of five characteristics for women and six characteristics for men identified approximately 80% of infections while testing ≤50% of the population. Information regarding race/ethnicity dramatically affected algorithm performance.CONCLUSION-Using race/ethnicity in any screening algorithm is problematic and controversial, but the model without race information missed many diagnoses in the minority groups. Universal screening in high prevalence regions and selective screening in low prevalence regions may be one method of reaching the affected populations while avoiding the stigma of guidelines incorporating race/ethnicity.Chlamydia trachomatis, with an estimated three million new infections each year, is the most common bacterial sexually transmitted infection (STI) in the United States (US), especially among adolescents and young adults (1). Black, Native American, and Latino women and men are disproportionately burdened with infection (2). Although predominately asymptomatic