Various disciplines use models for different purposes. While engineering models, including software engineering models, are often developed to guide the construction of a non- existent system, scientific models, in contrast, are created to better understand a natural phenomenon (i.e., an already existing system). An engineering model may incorporate scientific models to build a system. Both engineering and scientific models have been used to support sustainability, but largely in a loosely-coupled fashion, independently de- veloped and maintained from each other. Due to the in- herent complex nature of sustainability that must balance trade-offs between social, environmental, and economic con- cerns, modeling challenges abound for both the scientific and engineering disciplines. This paper offers a vision that synergistically combines engineering and scientific models to enable broader engagement of society for addressing sustain- ability concerns, informed decision-making based on more- accessible scientific models and data, and automated feed- back to the engineering models to support dynamic adap- tation of sustainability systems. To support this vision, we identify a number of research challenges to be addressed with particular emphasis on the socio-technical benefits of modeling.