This chapter presents and discusses two complementary statistical approaches for analyzing trajectories in a life course perspective: Sequence analysis and Markovian models. Sequence analysis is an exploratory approach that focuses on the entire trajectory and aims to identify similar patterns among individuals. Markovian models are instead model-based approaches. In a Markovian perspective, life trajectories are seen as the result of a stochastic process in which the probability of occurrence of a particular state or event depends on its history. The goal is then to identify the data generating process beyond the observed sequence of states. We demonstrate the differences and the complementarities of both approaches for studies on the inequality over the life course with an empirical illustration using retrospective data on life trajectories in Switzerland from age 20 to 65 in three life domains: health status, family situation, and working life. The data are collected in 2013 as part of the Swiss Household Panel study.