Obviously, machine learning applications are being used more and more in a wide variety of fields. The general rule today is that in the absence of analytical models, one always turns to machine learning. In itself, machine learning has become synonymous with artificial intelligence. The reverse is also true – artificial intelligence today is machine learning. Sometimes this definition is somewhat limited, and they only talk about artificial neural networks and deep learning in the context of artificial intelligence, but this does not change the essence of the matter. At the same time, it is also obvious that the spread of machine learning technologies leads to the need for their application in the so-called critical areas, where there are special requirements for confirming the operability and quality of software. These areas include, for example, avionics, nuclear power, autonomous vehicles, etc. Audit and, of course, certification are the procedures for evaluating machine learning models. – from our new paper