Recruiting high-risk, HIV-negative participants is challenging for HIV prevention trials. This study aimed to 1) identify and characterize subsets of high-risk women based on responses to demographic and psychosocial questions from the AIDS Indicator Survey (AIS) and 2) develop a rapid, inexpensive tool for site identification. We developed a latent class model (LCM), hypothesizing that AIS respondents could be grouped by responses to psychosocial indicators, and that these latent classes would vary by HIV status, socio-demographic, and other indicators. We tested our model on women respondents from the Tanzania 2003 AIS Survey, and replicated it in several other populations. LCM produced four classes of women who significantly varied by psychosocial indicators and HIV status. Geographic differences in HIV prevalence and class composition were observed. Our approach has the potential to provide a more systematic, inexpensive and rapid strategy to identify HIV prevention trial sites.