The newly emerging science of Human-Centric Functional Modeling provides an approach towards modeling biological and other systems that is hypothesized to maximize human capacity to understand and navigate complexity in those systems. This paper provide an overview exploring how Human-Centric Functional Modeling might be applied in evolutionary biology, and how this increase in capacity to understand the complexity that organisms have evolved into might be achieved. The broader usefulness of Human-Centric Functional Modeling is that it provides a simple mathematical definition of what constitutes a biological system, defines the problem-solving domain of any biological system in terms of abstract mathematical spaces, and provides an expression defining general problem-solving ability in any such domain. This enables it to be seen that all systems with general problem-solving ability in their own domain are potentially an abstraction of a single mathematical pattern of adaptive problem-solving that might apply to all domains. From this perspective nature has already potentially solved problems in biological organisms that can be represented in some abstract functional state spaces as the same general problem that must be solved to address problems in a wide range of other systems, including existential challenges from poverty to climate change, where Human-Centric Functional Modeling enables it to be seen that not only can nature’s solutions be copied, but that nature has demonstrated its solutions to have worked for hundreds of millions of years.