Purpose. Enhancing operational efficiency of natural gas pumping units by applying artificial intelligence methods to assess their technical condition.Methodology. The artificial neural networks theory, in particular, the counterpropagation network with two layers of Kohonen and Grossberg, was used to recognize aggregate states. The structure choice and calculation of the separation line coefficients was carried out using genetic algorithms.findings. The task of evaluating the aggregate technical state is formed as a pattern recognition task. An analysis of literary sources has shown that the problem of pattern recognition relates to difficulttoformulize tasks, and their solution requires new approaches, based on artificial intelligence methods. The artificial neural networks of counter propagation are proposed to use for recognizing the aggregate technical states. The article shows advisability of using the LVQnetwork type, which has two layers of Kohonen and Grossberg in its composition, for this assessment. The efficiency of the network is confirmed by a test case. A ge netic algorithm that allows choosing both the polynomial structure and its parameters is used to construct a diving line separating one class of signs from another. The technical condition of the lubricating system of the natural gas pumping aggregate is esti mated, as an example of the developed methodology application.originality. The AIbased method for assessing the technical state of gaspumping units has been further developed to evaluate their state in operating mode and, based on this, develop effective algorithms for optimal loading of parallel operating aggregates.Practical value. Algorithmic and software testing was developed on the test case, based on the proposed method for assessing the aggregate technical condition. The proposed method, which effectively solves the problem of partitioning the signs planes into classes each of which characterizes its certain state, has been shown as an example of the technical state evaluation of the gas tur bine engine lubrication system.