In this study, hexose ( glucose) and pentose ( xylose) in mixture solutions were substituted with anthrone, and their spectrophotometric absorbance values at 540 nm were recorded. MATLAB software was applied for data treatment as a multivariate calibration tool in the spectrophotometric procedure. The artificial neural network (ANN) trained by the back-propagation learning was used to model the complex relationship between the concentrations of hexose and pentose and the absorbance values of sugar mixture solutions. The optimized network predicted the hexose and pentose amounts in the mixture solutions. The ANN used can be proceed the data with an average relative error of less than 1.40%. Furthermore, the hexose and pentose amounts of pine wood sample were estimated by ANN and compared with gas chromatographic results of the same sample. The percent differences between predicted and gas chromatographic results were found as 6.62% for pentose and 1.44% for hexose, respectively.