Early-stage evaluation of biofuel and bioproduct technologies is extremely complicated and involves many disparate feasibility criteria, including technical, financial, environmental, logistic, legal, social, and other aspects. Problems can arise for decision-makers when evaluating renewable technologies at this early stage due to bias, shifting preferences or priorities, occurrence of trade-offs, and decision-making complexity. Thus, a method is needed for evaluating disparate, typically non-comparable criteria concurrently. In Part 1 of this research, cradle-to-grave environmental LCA was conducted for biomass delivery to a biosugar refinery using Ecoinvent v2.2 data and the TRACI 2 impact assessment method for midpoint impacts. Biomass availability, delivered cost, sugar yield, transportation distance, harvestable months per year, and other aspects of supply chain feasibility were measured for eighteen feedstock biomass types. In Part 2, stochastic multi-attribute analysis (SMAA) was used alongside LCA to develop an environmental preference single-score probability distribution function for feedstock alternatives. Weighted single-scoring and ranking, using multi-criteria decision-making analysis (MCDA), was conducted considering five criteria of biomass supply feasibility: biomass delivered cost, biosugar yield, harvestable months, transport distance, and environmental preference single-score. Corn was shown to cost the most, followed by switchgrass and U.S. primary forest products. Transport distance was found to be highest for residues due to low yield per acre and low covered area. Results of MCDA show that Brazilian eucalyptus and Malaysian empty fruit bunch biomass types were consistently preferred relative to other biomass types. In the U.S., Genera biomass sorghum is most holistically preferred. It is shown that SMAA is helpful for translating LCA data for decision science. It was shown that MCDA can be useful for early-stage biorefinery technology commercialization decision-making, using the novel decision science tool described herein.