This research was aimed to explore the use of multivariate statistics i.e. principal componentanalysis (PCA) in identifying and integrating variables related to forage quality and ruminal methaneproduction, and in classifying forage species into both characteristics. Seventeen plants were used as adatabase for the above mentioned purposes. Plant samples were determined for their chemicalcomposition, cumulative gas production (represents the nutrient degradation) and methane productionafter 24 hours of fermentation period using the Hohenheim gas test. The results showed that the PCAcould clearly identify factors related to forage quality and methane production and separated them intodifferent principal components (PC). The obtained PC1 was related to methane production andsubstantially influenced positively by crude protein, NDF, ADF (positive), total phenols, total tannins,condensed tannins and tannin activity (negative). On the other hand, the obtained PC2 was related tocumulative gas production (forage quality) and substantially influenced by crude protein (positive),NDF, ADF and condensed tannins (negative). Classification and screening of forages that have highquality and low methane production are possible using the PCA technique. Rhenum undulatum,Peltiphyllum peltatum and Rhus typhina were found to have such desired characteristics.