The purpose of this study was to investigate special education outcomes in relation to state standardized testing. It specifically sought to determine if a relationship existed between selected data from the Texas Academic Excellence Indicator System (AEIS) comparing district students receiving special education services TAAS scores with selected district demographic, fiscal, and special education data. The population for this study consisted of all 2001-2002 grades 3-8 and 10 public school students with the exception of charter schools, special-purpose statutory districts, and state-administered districts. The reading analysis incorporated data from 896 Texas school districts. The mathematics analysis used data from 914 school districts. Multiple linear hierarchical regression was chosen as the method for statistical analysis. Data was obtained from the Texas Education Agency (TEA) as a special data pull. For both the reading and mathematics analyses, wealth and ethnicity were statistically insignificant although ethnicity individually accounted for a large percentage of the variance for both the reading (20.3%) and mathematics (13.2%) scores as well as producing negative β weights. All other predictor variables produced varying degrees of statistical significance. Community type, socioeconomic status, instructional expenditures per students, and instructional expenditures per student receiving special education services also produced negative β weights. Two variables in this study, enrollment and the percentage of students receiving special education services tested, produced positive β weights, substantial squared structure coefficients, and positive Pearson correlation coefficients. Of these two predictors, the strongest overall positive predictor for students receiving special education services success on the grades 3-8 and 10 reading and mathematics TAAS exams was the percentage of students receiving special education services tested. These percentages produced the largest positive correlations with passing rates (reading r = .283, mathematics r = .219) and the second largest regression coefficients (reading β = .224, mathematics β = .202). They individually accounted for the largest percentage of total criterion variance (reading = 33.0%, mathematics = 22.6%). For this study, these results clearly suggested that the dominant positive predictor of testing success for students receiving special education services was the percentage of students receiving special education services tested. Conversely, socioeconomic status was the dominant negative predictor.