Abstract <p>This article considers the use of artificial neural networks to analyze various defect combinations in removable load-handling devices and make decisions regarding their continued suitability for use. Statistical databases of expert assessments are used to train the artificial neural networks. An artificial neural network model has been developed that takes into account various defect combinations based on the deviation of the geometric parameters of the removable load-handling device from design values. It can be used to assess the performance of various types of removable load-handling devices, consisting of elements considered in the input layer of the neural network. The influence of the operating factors of removable load-handling devices on the confidence levels for determining their technical condition is demonstrated.</p>