Summary. We compare two techniques that are widely used in the analysis of life course trajectories: latent class analysis and sequence analysis. In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of the classification that is obtained via the two techniques by using a data set on the life course trajectories of young adults. Then, we adopt a simulation approach to measure the ability of these two methods to classify groups of life course trajectories correctly when specific forms of ‘random’ variability are introduced within prespecified classes in an artificial data set. To do so, we introduce simulation operators that have a life course and/or observational meaning. Our results contribute on the one hand to outline the usefulness and robustness of findings based on the classification of life course trajectories through latent class analysis and sequence analysis and on the other hand to illuminate the potential pitfalls in applications of these techniques.