The development of separation processes for polymers or proteins from aqueous solutions requires a high amount of experimental effort, including phase-equilibrium data such as solid-liquid, liquid-liquid or vapor-liquid equilibria. This effort can be reduced by means of thermodynamic models. This work presents a new method for parameter estimation and validation of thermodynamic models by means of static-light-scattering (SLS) measurements. In this work the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) was used to predict directly the SLS data (Rayleigh ratio) of macromolecular solutions. In a first step, SLS data were measured for binary water/polyethylene glycol (PEG molecular weight ranging from 2000 to 12000 g/mol) mixtures and for binary water/lysozyme mixtures. Applying pure-component PC-SAFT parameters from literature, the SLS data of these binary mixtures were successfully predicted with PC-SAFT. In a second step, one binary interaction parameter between lysozyme and PEG was adjusted to new experimental SLS data of buffered PEG/lysozyme/water solutions with PEG6000 concentration of 20 g/L. Finally, SLS data for buffered ternary PEG/lysozyme/water solutions with PEG of different molecular weights (2000-12000 g/mol) and different concentrations (1-50 g/L) were accurately predicted with PC-SAFT. Thus, (1) the proposed approach allows predicting SLS data, and (2) the method provides an access to the estimation of model parameters by means of experimental SLS data, which are accessible with much less effort than experimental phase-equilibrium data. (C) 2018 Elsevier B.V. All rights reserved.