Most interesting phenomena in natural and social systems include transitions and oscillations among their various phases. A new phase begins when the system reaches a threshold that marks a qualitative change in system characteristics. These threshold effects are found all around us. In economics, this could be movement from a bull market to a bear market; in sociology, it could be the spread of political dissent, culminating in rebellion; in biology, the immune response to infection or disease as the body moves from sickness to health. Complex Adaptive Systems (CAS) has proven to be a powerful framework for exploring these and other related phenomena. Our hypothesis is that by modeling differing complex systems we can use the known causes and mechanisms in one domain to gain insight into the controlling properties of similar effects in another domain. To that end, we have created a general CAS model; one that is flexible enough so that it can be individually tailored and mapped to phenomena in various domains, yet retains sufficient commonality across applications to facilitate a deeper, cross-disciplinary understanding of these phenomena. In this work, we focus on the threshold effect. We show that the general model successfully replicates key features of a CAS. And we demonstrate its general applicability by adapting the model to three domains: cancer cells and the immune response; political dissent in a polity; and a marine ecosystem.