Production of ethanol from biomass has been a subject of extensive research. To date, a variety of different pre-treatment technologies have been identified that render lignocellulosic biomass accessible for ethanol production. The hydrolysate that is formed during this pre-treatment process contains degradation products which may decrease the fermentability of the hydrolysate. Fermentability can be measured in several ways. Typically, batch fermentation studies are carried out, followed by comparison of results to a control which contains only the fermentation medium and microbe. These methods are time consuming and labor intensive which makes them unattractive to researchers. We are currently exploring a novel way to predict fermentability of hydrolysates based on chemometric modeling of spectroscopic data. Twenty pretreatment conditions, resulting in hydrolysates of variable composition, were selected for model development and validation. For each hydrolysate, spectroscopic information and relative fermentability were determined in independent experiments.  These data were then evaluated chemometrically, using commercially-available software, in an attempt to identify the degree of correlation and predictive capabilities of models that varied with respect to the type of spectroscopic information and/or chemometric approach utilized.