Demonstrating causal effects in developmental studies is important if results are to guide programs and policies that improve the lives of children and families. Yet, human development is complex and dynamic, and researchers are often limited to correlational data to answer their questions, which challenges the establishment of causal relations. In this article, we summarize potential threats to internal validity researchers encounter when analyzing correlational data and present several methods to strengthen internal validity. We suggest that developmental scientists consider using these methods in their studies to strengthen causal inferences and enhance the impact of their research.