In this paper we investigate the prediction of rheological properties of bitumens using some structural parameters calculated from C-13 NMR data. This study was carried out using methods of quantitative structure properties relationships (QSPR) and more particularly neural networks (NN). Such a mathematical tool can find out non linear relations between descriptors and properties. Two asphalt rheological properties, m (creep slope at low temperature) and G*/sin delta (stiffness at high temperature) were selected, whereas the descriptors are the average molecular parameters which characterize the hydrocarbon skeleton of bitumens. This work permitted to prove that the skeleton information contained in the average molecular parameters could be correlated to the m value but not to the G*/sin delta. Thus, the low-temperature rheological behavior appears to be highly dependent on the aliphatic part of the bitumens.