AbstractDue to the novel coronavirus COVID‐19 pandemic in 2020 and the stay‐at‐home orders that accompanied mandates for businesses to cancel in‐person activities, an increasing number of people turned to fitness alternatives that allowed them to exercise without leaving their homes. With this came a demand for at‐home workout solutions and a surge in sales for companies like Peloton and NordicTrack. To help determine the best solution for a potential customer, this paper analyzes a System‐of‐Systems to optimize a meta‐architecture for an at‐home spin class capability by maximizing five key performance attributes: affordability, efficiency, flexibility, enjoyment, and efficacy. The overall System‐of‐Systems was analyzed using a Fuzzy Inference System that interfaces with SoS Explorer, a System‐of‐Systems architecting tool developed by Missouri University of Science and Technology. A genetic algorithm guided the optimization process to generate a single meta‐architecture that provides the best possible value for the overall objective of the System‐of‐Systems. A summary of the simple Self‐Organizing Genetic Algorithm is included along with a definition of the constraints and equations used to define the score of the meta‐architecture given the combination of systems selected and their associated capabilities, characteristics, and feasible interfaces. Future work includes the expansion of the approach to other potential equipment and workout types, such as running, yoga, and lifting, as part of the analysis and optimization using SoS Explorer.