The effectiveness of a state-mandated set of at-risk criteria to predict which students are likely to become dropouts is evaluated in this study of the Austin Independent School District (AISD). Descriptions of the district information delivery system, state criteria, and criteria operationalization are provided. Discriminant function analysis indicates that state criteria correctly predicted 40 percent of the dropouts. Most of the differences between students who left school and those who stayed were not explained by the predictor variables. Categories developed from the state criteria were used to calculate a dropout risk rate, and it was found that age (i.e., the status of being 2 or more years older than the average for the grade level) was a common factor in all of the six highest risk categories identified, which consisted of age alone plus age in combination with five other state predictors. However, these combinations identified students with a dropout risk rate of less than 50 percent. Stepwise regression analysis identified three of the four state criteria as statistically meaningful: over-age; failing courses; and being below grade level. Recommendations are made for an expanded and more focused list of criteria, interdistrict research collaboration, and cohort analysis before the ninth grade. Tables and figures illustrate the study findings. (7 references) (LMI)