Inductive reasoning extends logic to decisions with uncertain and incomplete information. In the previous chapters, we learned how to codify information into probabilities, how to build consistent statements by assigning and manipulating probabilities, and how to evaluate and express measurement uncertainties. Now, we address the problems of updating probabilities when new information is available and assigning probabilities to models competing to explain the data.