Psychologists are often interested in understanding the processes through which a predictor transmits its effect to an outcome of interest. Generally, researchers focus on the sequential (statistical mediation) and conditional (statistical moderation) processes to explain the relationship between a predictor and outcome. In this workshop-style presentation, I will introduce conditional indirect effects models that integrate mediation and moderation to further our understanding of heterogeneity in psychological processes. Using an applied example, I will demonstrate how to estimate a conditional indirect effects model with the lavaan package and strategies for reporting the results. Feel free to listen and learn, or to bring along a laptop to follow along with analyses!