Irrespective of the goals of modelling, model-development process involves similar steps. It breaks the model-development process into six phases: business understanding, data understanding, data preparation, modelling, evaluation, and deployment. The three steps: data understanding, model assembly, and model audit, are often iterated to arrive at a point when, for instance, a model with the best predictive performance is obtained. The Model-development Process, proposed by Biecek, has been motivated by Rational Unified Process for Software Development. In this chapter, the authors provide a brief overview of the notation that will be used in the book, and the methods commonly used for data exploration, model fitting, and model validation. In the predictive modelling, the focus is on minimization of the sum of the (squared) bias and the estimation variance, because the people are interested in minimization of the prediction error.