Abstract: Based on the theory of uniform convergence of frequencies of events to their probabilities given by Vapnik and Chervonenkis, the relation-ship among the number of mapping functions, the size of training samples, and the ability of generalization of the multilayered neural network is discussed. The minimum training sample size, which guarantees valid generalization in the worst case, is analysed.