A multivariate calibration method for the characterization of heparin samples based on the analysis of (1)H nuclear magnetic resonance (NMR) spectral data is proposed. Heparin samples under study consisted of two-component or four-component mixtures of heparins from porcine, ovine and bovine mucosae and bovine lung. Although the (1)H NMR spectra of all heparin types were highly overlapping, each origin showed some particular features that could be advantageously used for the quantification of the components. These features mainly concerned the anomeric H, which appeared in the range 5.0-5.7 ppm and the peaks of acetamidomethyl protons at 2.0-2.1 ppm. The determination of the percentage of each heparin class depended on these differences and was carried out using partial least squares regression (PLS) as a calibration method. Prior to the PLS analysis, the spectral data were standardized using the internal standard peak (sodium 4,4-dimethyl-4-silapentanoate- 2,2,3,3- d (4), TSP) as the reference. The quantification of each heparin type in the samples using PLS models built with 4 or 5 components was satisfactory, with an overall prediction error ranging from 3% to 10%.