The procedures of comparative analysis using statistical criteria for evaluating the information content of radio sources of telecommunication networks and systems in their classification and recognition as a set of formalized rules for collecting, processing and analyzing the information obtained are considered. In the introduction, the general processes of recognition and classification of sources of radio emission of telecommunication networks are analyzed, the main statistical criteria for evaluating the information content of information features are given. It is noted that most of the mentioned criteria of recognition allow to carry out only ranking of signs and do not provide the solution of the problem of quantitative estimation of their informativeness by the criterion of minimum probability of error or maximum probability of true recognition. With this in mind, a research goal has been formed, which is to develop a procedure for comparative analysis using statistical criteria for evaluating the information content of radio sources of telecommunication networks and systems in their classification and recognition, as a set of formalized rules for collecting, processing and analyzing the information obtained. The study found that the exact value of the probability of error is difficult to obtain, since its estimation requires knowledge of decision thresholds. The integration in the calculation is only possible numerically. Therefore, in order to solve the recognition problem, it is advisable not to use the error probabilities, but their boundaries (upper and lower), which must be strict on the one hand and easily calculated analytically on the other. It should also be borne in mind that the probability of errors and their boundaries are uniquely related to the class distance (classes), which in turn must be clearly related to the probability of true recognition. Based on the analysis of analytical expressions of the statistical criteria for estimating interclass distances, recognition theory establishes mutual analytical relationships between the main criteria of interclass distances. It is substantiated and proposed to solve the problems of recognition by applying the Fali – Semmon transform, where the criterion of optimality is the maximum ratio of the mean differences of the projections of the vectors of the data of the classes to be recognized to the sum of the covariations in the middle of the classes in their projection to the parameter vector, resulting in a modified Fisher ratio. It is also determined that all the criteria considered are designed for a small number of recognition classes, whereas in practice the number of classes and their size is very large and their total number is unknown. Moreover, the recognition process is multi-parameter, which makes it difficult to solve the problems of classification and recognition of objects and sources of radio emission. To overcome this situation, it is proposed to use a criterion based on the coefficient of non-orthogonality of the conditional probability distributions of the probability of a trait, which can be considered as a