Since models in MDE are expected to get progressively more complete, precise and executable and be used to generate the code and other artifacts such as test cases, they may be used to evaluate and verify the quality of design, fix errors and eliminate unwanted complexity. MDE also adds new requirements to the development process such as consistency between models and technical comprehension by tools.Model-driven quality engineering and evaluation focus on integrating quality aspects into tools, modeling languages and activities such as transformations,monitoring quality and evaluating it during the course of software development. It could be more effective the earlier it starts and more models / activities it covers. We used the literature on transformations to show examples of goals, means and evaluation methods, and integrated them together to show that engineering and evaluating quality need to go hand in hand. Putting the goals together allows analyzing them for dependencies and verifying the set for completeness and orthogonality in future work.However, much work is still needed in all the stages defined in Figure 3. Suggestions for future work on transformations are further analysis of what affects the quality of transformations, how quality can be evaluated and how we can engineer models and transformations of high-quality. Especially important is the development of tool support for quality engineering, as tools are such an important part of MDE. This would support the operationalization part of the MDE quality framework. We will build further on the framework presented here to identify quality goals /means / and evaluation methods for other aspects that affect the quality of models and are relevant for our partners in the MODELPLEX project 28. One of such aspects is identifying quality criteria for Domain-Specific Languages (DSLs) appropriate for modeling large and complex systems.Acknowledgements. This research was done in the “Quality in Model-Driven