Since the late 1990s the nursing field has experienced increased demand for RN’s as well as a number of internal and external factors that have worsened this problem. College admissions officers have struggled to identify those students who are most likely to persist in an associate degree nursing (ADN) program. Estimates of programmatic attrition vary, but fall somewhere between 25-50%. A great deal of research has been expended in an attempt to determine which preadmission variables are most likely to indicate programmatic success. Unfortunately, no “best set” of admissions variables has been identified. The purpose of this research was to identify cognitive and noncognitive predictors of success in an ADN program. These variables can then be used by nursing program administrators to help identify students during the admissions phase who are most likely to persist through the first term and potentially to degree completion. Bloom’s theory of school learning serves as the theoretical framework for this research. The participants in this study were 188 students (summer and fall cohorts) in the Associate of Science in Nursing (ASN) program at a large state college in the southeastern region of the United States. The research design was a quantitative, non-experimental, correlational design to predict the relationship between four input predictor variables and one criterion variable. The Health Education Systems Inc A2 assessment (HESI A2) and the Grit-S Scale were used to measure these input variables. Binary regression was used to analyze the resulting data. This research is critical in addressing nursing shortfalls, a pressing real world problem facing society at large, nursing in general, and college admissions departments for ADN programs in particular.