Universities consist of students, faculty and staff, interacting through multiple layers of organization and on a variety of time scales. They are complex adaptive systems (CAS) yet the bulk of scholarship on higher education analyzes them using conventional social science methods, with little work that tries to understand them using complexity tools and methods such as agent-based models. Here I take a CAS approach. I first explore the sizes of U.S. universities and document significant positive correlation among important variables like acceptance rates, locations in urban/rural settings, the presence of law and medical schools, research and development expenditures, and sizes of host cities/locales. Next, I use computational social science (CSS) ideas to look for signatures of complexity in data on U.S. universities. Specifically, power-law size distributions are found in certain financial aspects of university performance -- the distribution of endowments. Finally, I develop a computational ABM that reproduces some of these patterns of size and growth of universities, based on R&D expenditure and interactions among competing universities. This research demonstrates, both empirically and computationally, that new and dynamic methods can be used to study universities. It shows how agent-based models can be used to explore questions related to university growth and the interactions between the environment and various university characteristics. This dissertation argues that static, equilibrium methods are ill-suited for modeling the heterogeneous behaviors of universities. It highlights how public policy planners, legislatures, and university administrators might better manage universities to achieve their stated goals. This approach takes a step toward providing university decision-makers with modern computational tools that can be used for 'what if' type analyses, leading toward more informed decisions, thereby shaping the future of higher education. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]