Publisher Summary This chapter focuses at improving a model, which assumes that at least a model exists. Moreover, the chapter discusses the process of turning the initially created model into one that better fits the data and the business problem. Although most of the processes apply as much to improve an explanatory model, as well as to improve a classificatory model, most of the issues are addressed as if the model to be improved is classificatory—except, where the issues discussed are specific to one type of model or the other. The process of improving model can be divided into two categories- (i) Discovering where the model has problems. (ii) Fixing the discovered problems. Refining the model is an important part of the data mining process. Refining requires methods for checking a model's performance, insight for understanding what the checks reveal, knowledge of what applicable techniques are relevant to improve model performance, and methods for applying the techniques to modeling data, or business problems, as appropriate. This chapter also explores the methods of diagnosis to identify problems with examples, and provides methods to apply the techniques to solve those problems. Insight and understanding come only with practice and repetition.