This thesis develops a modeling framework for the pricing of a synthetic Collateralized Debt Obligation on Asset-Backed Securities (CDO on ABS) and other credit derivatives on ABS. A credit derivative with ABS exposure has attracted much attention in recent years. As one of the latest innovations in the financial market, a credit derivative on ABS is different to the traditional credit derivative in that it sources credit risks from the ABS market, for example the Sub-Prime mortgage market, rather than from the market for corporate default risks. The traditional credit risk models are all designed for corporate default risks however they do not cover some of the unique features associated with an ABS. Motivated by this modeling discrepancy, in this thesis we design a credit risk model for the pricing and risk management of credit derivatives on ABS. The thesis starts with an introduction to some related products and markets. The difficulties in the construction of a pricing model for credit derivatives on ABS are outlined and some basic concepts are introduced to simplify the problem. The foundation of the model is based on a reduced fonn approach, where defaults are driven by an explicit intensity. A prepayment intensity is also introduced to drive the dynamics of the future cash flow of an ABS asset. For multiple name products such as a CDO on ABS, we model the default and prepayment dependency between each of the single name assets via a copula approach, where the interdependency of default and prepayment of each single name asset is also dynamically captured in an integrated framework. A semi analytical solution is derived for the model via a Fourier transfonn method. Some variance reduction techniques are also examined for an efficient Monte-Carlo implementation of the model for pricing and risk calculation purposes. A traditional credit derivative can also be priced as a special case within our modeling framework.