Diagnostic Classification Models (DCMs) are aimed to classify subjects based on latent attributes. They can produce more detailed information to facilitate teaching and learning. This paper introduces DCM models in a non-technical way. The first half covers the main components of DCM models, differentiates between compensatory versus non-compensatory models and explains the meaning of some common parameters. The second half introduces an application by Eunice Jang (2005; 2007) in a language testing and teaching situation. The study demonstrated the complete procedure in how to apply a DCM model. The accuracy and advantages of the model were clearly revealed. The value of the DCM model, however, depended on the teachers’ perception of the model and results. The author of this paper further elaborated on issues and challenges for DCMs.