A rigorous model supported by botanical investigations has been developed to predict percolation results. Botanical investigations provide needed modeling parameters like pore size, porosity, or target compound distributions over the particle. After determining the desorption isotherm with maceration experiments at different solvent-feed ratios, the model is validated with short residence time percolation experiments. With the aid of this validated model, percolation experiments with long residence times can be predicted and different process scenarios calculated. A combination of design of experiments and rigorous modeling together with standard equipment and experimental model parameter determination provides a fast and robust experimental design on the one hand and the precondition for a process parameter data-based learning curve on the basis of rigorous modeling in the mid- or long-term on the other hand.