An artificial neural network (ANN) is proposed, which allows to make express-analysis of the chemical composition of production objects metal-containing materials in automatic mode with high accuracy and real-time performance. The proposed ANN for automatic recognition of chemicals (ANN ARoC) is an alternative to traditional high-cost and time-consuming physical and chemical methods and labelling analysis, which are significantly complicate and slow down technological processes, as well as environmentally hazardous to human health and environment. The mean square error of proposed ANN ARoC does not exceed 5%, the time of determining the chemical composition of production objects metal-containing materials is not more than 2.5 s. ANN ARoC is built on the principle of a multilayer perceptron with a tunable structure of neurons and practically implemented in the form of an appropriate software product. The latter ensures its versatility in terms of the possibility of retraining and readjustment when new tasks arise in accordance with the rapidly changing conditions of modern dynamic production.