F. K. Del Boca, J. Darkes, P. E. Greenbaum, and M. S. Goldman (2004) examined temporal variations in drinking during the freshmen college year and the relationship of several risk factors to these variations. Here, using the same data, the authors investigate whether a single growth curve adequately characterizes the variability in individual drinking trajectories. Latent growth mixture modeling identified 5 drinking trajectory classes: light-stable, light-stable plus high holiday, medium-increasing, high-decreasing, and heavy-stable. In multivariate predictor analyses, gender (i.e., more women) and lower alcohol expectancies distinguished the light-stable class from other trajectories; only expectancies differentiated the high-decreasing from the heavy-stable and medium-increasing classes. These findings allow for improved identification of individuals at risk for developing problematic trajectories and for development of interventions tailored to specific drinker classes.