This paper illustrates the features of a computational framework which implements an approach to the automated modeling of the rheological behavior of viscoelastic materials. Qualitative, symbolic, and quantitative techniques are integrated to make the most of the available knowledge, and automate model formulation with the goal of attaining both computational efficiency and result accuracy. We used the tool to explore the mucoadhesive potential of pharmaceutical polymers. Solutions of NaCMC polymers and polymer-mucin mixtures at different concentrations underwent standard creep tests, and accurate ODE models were obtained from the data. Model order and parameter values, which are related to the number of structural units within the polymeric network and their strength, respectively, characterize the material complexity and provide a measure of its mucoadhesive potential. Compared with a purely experimental investigation, the model-based approach is cheaper and produces insights into the mechanisms of polymer-mucus interaction.