Contents: 1. Introduction. 2. Key aspects of decision modelling for economic evaluation. 3. Further developments in decision analytic models for economic evaluation. 4. Making decision models probabilistic. 5. Analysing and presenting simulation output from probabilistic models. 6. Decision-making, uncertainty and the value of information. 7. Efficient research design. 8. Future challenges for cost-effectiveness modelling of health care interventions. In financially constrained health systems across the world, increasing emphasis is being placed on the ability to demonstrate that health care interventions are not only effective, but also cost-effective. Decision must be made on issues such as medical devices, diagnostic technologies, surgical procedures, and Pharmaceuticals. Researchers are therefore required to incorporate all technologies with the alternative options, and to reflect uncertainty in evidence in the conclusion of the analysis. Decision-analytic modeling is commonly used as the framework for meeting these requirements. This is a practical guide to the use of modeling techniques, starting with the basics of constructing different forma of model, the population of the model with input parameter estimates, analysis of the results, and progression to the holistic view of models as a tool to inform future research exercise. Key techniques and approaches are discussed, and a comprehensive set of example exercise take the reader through how to conduct decision analytic modeling. These exercise are supported with templates and solutions made available via the book website.