Sterilizing filtration is a common unit operation for the manufacture of parenteral drug products. However, filter performance can be impacted by properties of both the membrane material and the solution being filtered, requiring extensive multi-factor studies to optimize the filtration process for a given drug product. Here, we report the use of a modified bundle of capillaries approximation to predict filter performance. The model is directly applicable for both Newtonian and non-Newtonian solutions and does not require assumptions of steady state. Using a hydrophilic polyvinylidene difluoride (PVDF) filter as a test case, we show that the model fitting parameters align with expected values and both flux and shear are well predicted. Moreover, two case studies are presented to demonstrate the model's utility for filtration process optimization: 1) protein adsorption of an antibody formulation and 2) filter fouling of a 1% (w/v) carboxymethylcellulose (CMC) solution. In both cases, the model was able to accurately identify optimal filtration parameters to reduce the amount of adsorption or improve the filter capacity, respectively. This methodology can be easily extended to alternate filter types and provides an additional predictive tool to speed process development and minimize trial and error during filtration process design.