Publisher Summary Credit risk is the single most important risk for a large number of financial institutions. This chapter defines credit risk and analyzes how a bank might classify its borrowers, evaluate the expected and unexpected losses that may derive from its credit portfolio, and calculate credit risk value at risk (VaR). A credit risk management system can consider different sources of losses, depending on the valuation methodology used, which can be based either on a mark-to-market (MTM) approach or on a book-value accounting (BVA) approach. When measuring the impact of credit risk, the bank has to estimate the distribution of potential losses that can be generated by its credit portfolio. The two key concepts are represented by expected losses, i.e., the statistical mean of the loss distribution, and unexpected losses, which can be defined as the amount of losses in some extreme percentile of the loss distribution minus expected losses. The main determinants of the dynamics of the expected and unexpected losses for a given exposure are represented by exposure at default (EAD), probability of default (PD), and the ratio of the loss in the event of default to the exposure at default, i.e., the loss given default (LGD). The chapter also discusses how LGD can be measured and the issue of the interaction of Basel II and the new international accounting standards, which emphasize the concept of incurred loss as a condition to register a reduction in a loan or loan portfolio value. While many banks use internally developed models rather than one of these vended models, even internal models often either resemble the logic or are partially based on the outputs of one of these four different approaches to credit portfolio modeling.