This paper introduces the RECA Model, a novel theoretical framework for the structural representation of algorithmic complexity through Layered Architectures. Departing from traditional computational models, RECA focuses on the internal organization of the state space using the R Tuple defined as R=(S,C,ϕ,Ξ). The research proposes that complexity is a structural property that can be optimized through hierarchical selection, providing new insights into the P vs NP problem by formalizing how layered selection operators can reduce search spaces. The RECA Model is designed for independent researchers and computer scientists looking for alternative paradigms in computational theory.