The retention of associative polymer molecules poses a significant challenge for its transport in porous media, and this arises due to the hydrophobic interactions that exists between the retained molecules. The known experimental approach in literature for quantifying polymer retention under static or dynamic conditions reports a generalized outcome without adequate estimates for each type of retention mechanisms. Thus, an accurate quantitative description of the various retention mechanisms (monolayer adsorption, multilayer adsorption and entrapment) attributable to associative polymers is crucial for proper optimization of its transport in porous media. In this work, a novel predictive approach was developed for quantitative mapping of the various retention mechanisms connected with associative polymers. The basis was a first-principles method adopted in mapping static to dynamic retention. This novel approach was achieved by relating the characteristic time scale for static and dynamic retention to the variation in polymer and reservoir properties, thus making it possible to correlate static retention results to large-scale dynamic retention with minimal fitting parameters. Furthermore, the mapping of the static to dynamic retention ensured an accurate quantification of the different retention mechanisms attributable to associative polymers. In this model, the in-situ entrapment was linked to the effective pore radius and the hydrodynamic size of the polymer molecules. Entrapment of polymer molecular aggregates was predicted based on the assumption that this occurs when the hydrodynamic size of the molecules becomes equal/greater than the effective pore size in the porous media. In addition, a threshold concentration value was estimated from which mechanical entrapment of polymer molecules would occur in a porous media alongside adsorption on pore surface. Similarly, a concentration value was estimated at which entrapment of polymer molecules becomes the dominant retention mechanism in the porous media.