Contrast analysis is a relatively simple but effective statistical method for testing theoretical predictions about differences between group means against the empirical data. Despite its advantages, contrast analysis is hardly used to date, perhaps because it is not implemented in a convenient manner in many statistical software packages. This tutorial demonstrates how to conduct contrast analysis through the specification of the so-called L (the contrast or test matrix) and M matrix (the transformation matrix) as implemented in many statistical software packages, including SPSS and Stata. Through a series of carefully chosen examples, the main principles and applications of contrast analysis are explained for data obtained with between- and within-subject designs, and for designs that involve a combination of between- and within-subject factors (i.e., mixed designs). SPSS and Stata syntaxes as well as simple manual calculations are provided for both significance testing and contrast-relevant effect sizes (e.g., η2 alerting). Taken together, the reader is provided with a comprehensive and powerful toolbox to test all kinds of theoretical predictions about cell means against the empirical data.