A predicament that engineers who wish to employ Bayesian networks to solve practical problems often face is the depth of study required in order to obtain a workable understanding of this tool. This chapter is intended as a tutorial material to assist the reader in efficiently understanding the fundamental concepts involved in Bayesian network applications. It presents a complete step by step solution of a bioinformatics problem using Bayesian network models, with detailed illustration of modeling, parameter estimation, and inference mechanisms. Considerations in determining an appropriate Bayesian network model representation of a physical problem are also discussed.