Solving the Navier-Stokes equations using direct numerical simulation (DNS) is computationally impractical, especially at high Reynolds numbers. Recent technological advances in supercomputing have paved the way for Large Eddy Simulations (LES) to circumvent this problem by resolving large scale turbulence motions and modeling only the small (subgrid) scales. However, LES modeling still requires advanced knowledge of the turbulence and LES models are currently very simplistic. Because of this, there has been considerable interest in hybrid turbulence models, which can perform either Reynolds Averaged Navier-Stokes (RANS) modeling or Large Eddy Simulation (LES). The self-adapting model presented is fundamentally different from prior LES models and these current hybrid models in that it achieves a completely natural evolution from RANS to LES to (with enough mesh resolution) DNS. A modified k/e model and a Reynolds stress transport model is implemented in this manner and is compared to DNS data of isotropic decaying turbulence. The results indicate that this modeling approach is practical and efficient. In addition, this approach is extensible and not restricted to a particular (RANS) transport equation.