This document provides an introduction to clinical decision modeling. It defines a decision model as an intellectual template for organizing business logic behind decisions. Decision models allow leveraging existing information, save time, and enable computers to perform complicated analysis. The document discusses using classification and clustering algorithms in decision modeling and compares how humans and computers approach decision making. It notes some challenges in decision modeling like overfitting, imbalance, and missing data, but emphasizes computers' advantages in feature selection and impartiality. The document encourages knowing the data well, using a gold standard outcome variable, employing existing modeling tools, and involving statisticians.