NOVELTY - The method comprises: providing (16) lignin from a source, where the composition of the lignin is unknown; performing (18) a molecular spectroscopy to analyze the lignin; performing (20) a physical-chemical analysis to further analyze the lignin; determining (22) the composition of the lignin; and predicting (24) a biobased product produced from the lignin using the determination of the composition. The molecular spectroscopy is infrared spectroscopy, total reflectance infrared spectroscopy, Raman spectroscopy and/or UV-visible spectroscopy.    USE - The method is useful: for evaluating lignin to predict a biobased product including biobased chemicals, biofuels, biomaterials and lignin residues; and for controlling quality in a biobased product refinery operation, a commercial biomass fractionators operation, a pulp/paper mills operation, a cellulosic ethanol refineries operation and/or a sugar cane mill operation, where the lignin is obtained from woody plant biomass, agricultural plant biomass and cultivated plant biomass, fresh plant biomass, recovered plant biomass, pulp and paper mill biomass, cellulosic ethanol refinery biomass, sugar cane mill biomass, kraft pulp mill, sulfite pulp mill, soda pulp mill, cellulosic ethanol refinery, commercial plant biomass fractionator biomass, lignin residues biomass, waste lignin including kraft pulp mill waste lignin, sulfite pulp mill waste lignin, soda pulp mill waste lignin, cellulosic ethanol refinery waste lignin, commercial plant biomass fractionator waste lignin, and sugar cane mill waste lignin (all clamed).    ADVANTAGE - The method is capable of predicting the biobased product with an accuracy of 85-100%.    DETAILED DESCRIPTION - The method comprises: providing (16) lignin from a source, where the composition of the lignin is unknown; performing (18) a molecular spectroscopy to analyze the lignin; performing (20) a physical-chemical analysis to further analyze the lignin; determining (22) the composition of the lignin; and predicting (24) a biobased product produced from the lignin using the determination of the composition. The molecular spectroscopy is infrared spectroscopy, total reflectance infrared spectroscopy, Raman spectroscopy, UV-visible spectroscopy, luminescence spectroscopy, fluorescence spectroscopy, mass spectroscopy, diffuse reflectance spectroscopy, transient spectroscopy, homonuclear magnetic resonance spectroscopy, heteronuclear magnetic resonance spectroscopy and/or two-dimensional nuclear magnetic resonance spectroscopy. The physical-chemical analysis is appearance analysis, moisture content analysis, melting point analysis, melting point range analysis, molecular weight analysis, molecular weight distribution analysis, size exclusion chromatographic analysis, thin layer liquid chromatographic analysis, high performance liquid chromatographic analysis, gas chromatographic analysis, particle size analysis, chemical oxidation analysis, chemical derivative analysis, chemical methoxy content analysis, chemical degradation analysis, biodegradation analysis, photochemical degradation analysis, pH titration analysis, thermogravimetric analysis, differential scanning calorimetric analysis, dynamic mechanical analysis, rheological analysis, pyrolysis degradation analysis, residual carbohydrate analysis, residue on ignition analysis, heavy metals analysis, density analysis, x-ray diffraction analysis, x-ray powder analysis or elemental analysis. The lignin is analyzed to provide two experimental datums related to the composition of the lignin, where the experimental datum is processed manually or electronically. The lignin analyzing process further comprises performing a statistical analysis of experimental data using a manual computation, spreadsheet computation, website computation and/or statistical software computation methods on a calculator or a computer. The statistical analysis of experimental data comprises a regression analysis of experimental data, where the regression analysis is a linear regression analysis and a multivariant regression analysis. The regression analysis of experimental data is provided by linear least squares regression analysis, manual computation, spreadsheet computation, website computation and/or statistical software computation. INDEPENDENT CLAIMS are included for:    (1) a method for evaluating and processing lignin; and    (2) a method for evaluation of biomass feedstock.    DESCRIPTION OF DRAWING(S) - The diagram shows a flowchart of a method for evaluating lignin.    Providing lignin from a source (16)    Performing a molecular spectroscopy to analyze the lignin (18)    Performing a physical-chemical analysis to further analyze the lignin (20)    Determining the composition of the lignin (22)    Predicting a biobased product. (24)