A major form of data analysis in clinical child and adolescent psychology is multiple regression. This article reviews issues in the application of such methods in light of the research designs typical of this field. Issues addressed include controlling covariates, evaluation of predictor relevance, comparing predictors, analysis of moderation, analysis of mediation, assumption violations, outliers, limited dependent variables, and directed regression and its relation to structural equation modeling. Analytic guidelines are provided within each domain.