My project is a theoretical eco-evolutionary account of the complexification of the quantity estimation (QE) aptitudes in the animal kingdom. I wish to bring together all the sub-disciplines that deal with any aspect of QE in order to create a combined body of knowledge that can be used as bedrock for the implementation of a new kind of evolutionary analysis, which constitutes a full-bodied, rich and coherent tale of complexification. My basic premise is that quantity is omnipresent, highly useful information for survival and, as such, mechanisms that allow for its perception and processing have emerged, persisted and complexified during evolutionary history. By complexification I assume that in order to shift from one aptitude to the next, more cognitive elements need to be integrated. This process had shaped a continuum of different cognitive manifestations of QE ranging from quorum sensing at its origin and culminating in mathematics. I also argue that QE is a composite behavior utilizing independent cognitive pathways, which in turn serve as its foundation while simultaneously possessing contextually antagonistic and competitive functions. By “composite” I mean that in order to be able to relate to quantity, an organism already relies on other available perceptual and/or cognitive traits operating on the same stimulus. I consider these other traits to be the building blocks of QE. “Competition” means that the sheer utilization of these building blocks automatically offers them concurrently as a viable alternative solution to the task. This interweaving is the source of both the emergence of QE complexification (phylogenetically) and of its hindrance (ontogenetically). I also suggest a plausible mechanism behind the evolution of QE and claim it is guided by exaptation and neurological redeployment: old and new cognitive pathways vie for "processing rights" and exert selection pressure on each other. I will offer a new eco-evolutionary narrative, complete with ontogenetic and phylogenetic mechanisms that utilize neurological models and evolutionary theory. Then I will demonstrate how the proposed framework brings to the surface a new perspective of the evolution of cognition by using select examples.