Systems level change in mental health is a major and costly undertaking. Getting it right is often difficult and some bad decisions are hard to rectify. For these reasons, major system innovations should ideally be robustly tested prior to implementation using simulation based approaches. However, mental health is both complex and highly contextual. We are a long way from having a mental health “theory of everything” that describes the systems in which mental disorders emerge and are treated sufficiently well to reliably predict the potential impacts of a wide spectrum of policy and service design choices. Instead we have lots of disparate bits of theory in the form of simulation models, but these are often of limited generalizability beyond the spatiotemporal and decision contexts for which they were developed. Their utility to many decision makers, especially where regional commissioning approaches apply, is often limited. These simulation models can be resource intensive to produce, but the lack of common theoretical and technical frameworks and consistent meta-data descriptions limit the extent to which modellers can efficiently leverage the insights, algorithms and data of their peers. To help address this challenge, we have developed a framework to support open source development of mental health simulation models, along with supporting code libraries and data-packs. In this presentation we described this framework with four examples from work undertaken as part of Orygen’s economics work-stream. These four examples are simulation models of