In a collaborative effort with INL, SNL, and JBEI, predictive modeling was used to evaluate and optimize traditional pretreatment methods for biomass mixture compositions to maximize sugar yield and minimize furfural production. The collaboration encompassed compositional analysis of feedstocks, solids loading during pretreatment for mixed feedstock, enzymatic hydrolysis on unwashed solids, and sugar and furfural analysis. Predictive modeling could effectively identify the pretreatment catalyst and treatment conditions for an “optimal” biomass mixture and the optimal biomass mixture for a particular pretreatment system.