Three-layer feed-forward neural networks for the prediction of 13C NMR chemical shifts of alkanes through nine carbon atoms are used. Carbon atoms in alkanes are determined by 13 descriptors that correspond to the so-called embedding frequencies of rooted subtrees. These descriptors are equal to numbers of appearance of smaller structural skeletons composed of two through five carbon atoms. It is demonstrated that the used descriptors offer a very useful formal tool for the proper and adequate description of environment of carbon atoms in alkanes. Neural networks with different numbers of hidden neurons have been examined. Best results are given by the neural network composed of three hidden neurons. Simultaneous calculations carried out by the standard linear regression analysis are compared with our neural network calculations.