The demand for kidney transplants is growing and far outweighs the supply of kidneys. With approximately 20 percent of kidneys discarded each year, there is an opportunity to develop a methodology to analyze the key performance attributes of the complex kidney transplant system. This paper designs and analyzes a meta-architecture for the organ procurement system with a use case in the kidney transplant system. The complex systems and interfaces create emergent behavior that will affect the key performance attributes of Performance, Discard Rate, Observed over Expected Kidney Transplants, Affordability, and Acceptability. These key performance attributes, interfaces, and rules are developed from multiple interviews and events with the systems’ stakeholders. We used fuzzy membership functions to assess the performance of the systems and then optimized them using genetic algorithms. We chose two use cases with one donor and three donors to demonstrate the flexibility of the methodology to determine the meta-architecture for a given number of systems. The maximum overall value obtained for each system of systems and participating systems are shown on a map. Future work includes developing and integrating a system of systems simulation to determine the effect of policy changes on organ procurement systems.