Survival analysis handles time-to-event data. Classical methods, such as the log-rank test and the Cox proportional hazards model, focus on the hazard function and are most suitable when the proportional hazards assumption holds. When it does not hold, restricted mean survival time (RMST) methods often apply. The RMST is the expected survival time subject to a specific time horizon and is an alternative measure to summarize the survival profile. RMST-based inference has attracted attention from practitioners for its ability to deal with nonproportional hazards. SAS/STAT® software now includes methods for analyzing the RMST: you can use the new RMSTREG procedure to directly model the relationship between the RMST and covariates, and you can use the RMST option in the LIFETEST procedure to estimate the RMST and make comparisons between groups. This tutorial demonstrates these methods through examples. It also presents the rationale behind the RMST-based approach and compares it with the classical methods. A basic understanding of survival data analysis is assumed.