The Systems Engineering industry employs a large number of people from the neurodivergent community. This research is important because it explores how we can promote diversity through systems engineering. The challenge we face in the industry is finding ways to work on complex systems that are inclusive of different neurological processes. This paper begins by looking into the meaning of neurodivergence, which shows us different ways our industry can include that community. Extensive research on the neurodiverse community shows that many lean toward visual learning styles and strict rules. Using this information, the industry could use a data-driven approach to Model-Based Systems Engineering (MBSE) to help the neurodivergent community better understand systems engineering, specifically using a common ontology. This research highlights the ontology, Lifecycle Modeling Language, a structured and behavioral modeling language. Through a heavier focus on Data-Driven MBSE and a collective ontology across our industry, we can create opportunities and foster positive change from a new community with a new perspective.