In this chapter, we critically discuss contemporary approaches to infer identity statuses. We will focus on how identity statuses can be delineated through a person-centered approach (e.g., cluster analysis and latent class/profile analysis [LCA/LPA]). These methods can depict how multiple variables are configured within persons, capturing identity statuses as indicated by questionnaire data. We detail the theoretical rationale for deriving identity statuses using a person’s scores on identity processes. We focus on how these approaches integrate classic identity status research with more novel identity process research. We critically discuss the differences in the way that statuses are derived with structured interviews compared to questionnaires, debating what each of the approaches contributes. We also highlight how a person-centered approach for deriving identity status clusters can provide additional insights to identity status models. Next, we detail these procedures using concrete examples for cluster analysis and LCAs/LPAs. In this, we explain how identity status clusters were derived at the person-level, using participants’ scores on identity processes. For both techniques, we focus on a step-by-step description of how we depicted the identity statuses, also comparing the results of cluster analysis and LCA/LPA on the same dataset. Additionally, we present requirements, general concerns regarding person-centered approaches, and specific concerns for each technique. Last, we present limitations of this approach and detail directions for future research. We ground this discussion on the results of recent studies that depicted identity statuses through cluster-analytic procedures in different cultural in order to analyze differences and points of convergence.