Adsorption processes on surfaces is highly relevant in the industry since they allow specific characteristics to be obtained, from fixing materials such as paints to the efficiency of reactions on catalysts. Although this relationship can be estimated using the adsorption isotherms, there are practical problems associated with its obtention when it is about paint adsorption on walls: complex characteristics of the analyzed system since there is no fluid phase that is in contact with the surface (no concentration of adsorbate can be measured, as is done in traditional adsorption processes) In this case, a phase change occurs when the paint drying process takes place, so only the concentration of the pigment is known, and how it is distributed on the surface, this data is insufficient to build the adsorption isotherm. A stochastic model was obtained allowing the adsorption representation for coatings, estimating the equilibrium constant associated with the adsorption process and the distribution of active sites from the fractal dimension observed in the mesoscopic scale and adsorbate concentration at equilibrium. Two paint-coated surfaces were evaluated finding the adsorption value predicted from the use of the proposed model. From the morphology of the surface, predictive behaviors can be performed..