In the present paper, the authors provide an overview of new psychometric approaches to the measurement of change that are of interest to clinical psychology. Based on the distinction between models for measuring (1) situation-specific variability, (2) developmental changes, and (3) changes caused by interventions, approaches for both, continuous and categorical outcomes are discussed. A special focus is on new developments in the area of mixture distribution models (e. g., mixture distribution state-trait models, growth mixture models). These models allow for a classification of individuals according to their specific pattern of change. Finally, the authors show how mixture distribution models can be applied to detect a priori unknown subgroups of individuals who differ in their response to treatments.