This chapter introduces the analysis of covariance (ANCOVA) and the multivariate analysis of covariance (MANCOVA) as statistical techniques for comparing group means in language assessment research. The chapter starts with a brief description of the basics and assumptions of ANCOVA and/or MANCOVA and provides suggestions for reporting the results. Research articles that have used these techniques are reviewed from four major language assessment journals. Key issues in the application of ANCOVA and MANCOVA, such as assumption check and effect size reporting, are highlighted. A sample dataset derived from the 2009 Programme for International Student Assessment (PISA) with variables related to students’ reading performance is analyzed to demonstrate how ANCOVA and MANCOVA can be conducted using SPSS. Data analysis procedures, including model building and assumption checks, are described in the companion tutorial. The results of the demonstration study are then summarized and briefly discussed, providing an accessible overview of the application of ANCOVA and MANOVA in language assessment research.