Developmental scientists are often interested in subgroups of people who share commonalities in aspects of development; these subgroups often cannot be captured directly but instead must be inferred from other information. Mixture models can be used in these situations. Two specific types of mixture models, latent profile transition analyses and growth mixture models, are highly relevant to developmental science because they can identify subgroups of people who are similar in their patterns of change. This guide highlights foundational aspects of these two types of models and is intended for readers who have not previously conducted either an LPTA or a GMM, or perhaps no mixture model analyses at all. It includes four primary sections. The first focuses on understanding mixture models conceptually and applying that knowledge to identifying appropriate research questions. The second section addresses data requirements, including planning for data collection or evaluating the suitability of previously collected data, and data preparation. The third section focuses on conducting analyses, with step-by-step instructions and syntax, and the final section discusses presenting the results. I illustrate these concepts and procedures with an example data set and research questions derived from the Five Cs model of positive youth development.