While hazard analyses allow researchers to identify distributional changes over time, this powerful benefit is often underutilized. This article incorporates the shape parameter—in addition to level—into lognormal hazard models to examine recidivism patterns for individuals returning home from prison. Using a sample of adults released in 1994 from 15 state prison facilities, the results indicate that factors influencing the shape are both individual-level (race, age, prior arrest history) and jurisdiction-driven (prison admission type and state). While targeting the highest “risk” individuals is a well-established best practice, the present study suggests that reentry planners may benefit from focusing on groups undergoing change in the postrelease period in addition to those experiencing the highest hazard levels on average. Future research would benefit from incorporating the shape parameter into recidivism studies and including additional factors in shape analyses, such as social indicators, to further contextualize the reentry–recidivism relationship.