Using an educational data mining approach, first-year academic achievement of undergraduate nursing students, which included two compulsory courses in introductory human anatomy and physiology, was compared with achievement in a final semester course that transitioned students into the workplace. We hypothesized that students could be grouped according to their first-year academic achievement using a two-step cluster analysis method and that grades achieved in the human anatomy and physiology courses would be strong predictors of overall achievement. One cohort that graduated in 2014 (n = 105) and one that graduated in 2015 (n = 94) were analyzed separately, and for both cohorts, two groups were identified, these being "high achievers" (HIGH) and "low achievers" (LOW). Consistently, the anatomy and physiology courses were the strongest predictors of group assignment, such that a good grade in these was much more likely to put a student into a high-achieving group. Students in the HIGH groups also scored higher in the Transition to Nursing course when compared with students in the LOW groups. The higher predictor importance of the anatomy and physiology courses suggested that if a first-year grade-point average was calculated for students, an increased weighting should be attributed to these courses. Identifying high-achieving students based on first-year academic scores may be a useful method to predict future academic performance.