This document provides an introduction to choosing regression models. It discusses basic considerations like determining the purpose of the model, choosing appropriate predictors, and whether predictors or the outcome need transformation. Temporal sequence and prior knowledge are important factors in choosing predictors. The type of data, case ascertainment, and results of model fitting also influence predictor choice. Transforming predictors or the outcome can improve the model fit in some cases. The key is using statistical tools together with experience and understanding, not as a substitute for scientific insight.