The voltammetric behaviours of ascorbic acid（AA）,uric acid（UA） and dopamine（DA） were studied at glass carbon electrode.Well-defined volammetric oxidation peaks for the three compounds were obtained by differential pulse voltammetry（DPV） in pH 5.7 Britton-Robinson buffer.However,serious overlappings of individual voltammetric peaks were observed for the mixtures of these compounds,which were difficult to determine by normal methods.To facilitate the resolution of these complex voltammograms,different calibration models were investigated based on the different chemometrics methods,including principal component regression（PCR）,partial least squares（PLS），radial basis function-artificial neural networks（RBF-ANN） and principal component analysis-radial basis function-artificial neural networks（PCA-RBF-ANN）.The results indicated that the lowest relative prediction error（RPE） was obtained with the PCA-RBF-ANN method.The method was successfully applied in the analysis of synthetic mixtures and urine sample without separation and purification.The developed method was then applied in the analysis of the compounds with satisfactory results.