The design and development processes of gas turbine engines rely on the usage of mathematical models representing the physics of engine functioning processes. One way of increasing the validity of a mathematical model is its identification based on engine test results. The identification of mathematical models of modern power-generating gas turbine engines (GTEs) presents a demanding and time-consuming task due to the necessity to identify the main controlled engine parameters determined in the course of experimental studies depending on a large number of the parameters that are not controlled during the experiment. In this regard the actual direction of reducing the labour intensity of the process of mathematical model identification is using identification program complexes. The object of the study was to solve the problem of structural-parametrical identification of the power-generating GTE functioning model detailing the turbine flow path calculations to the level of blade rows in order to obtain the GTE mathematical model that describes the characteristics of a real engine with given accuracy. To achieve the objective, the following problems were solved: variable parameters, controlled parameters and characteristics, ranges of their variations were selected from the total number of the mathematical model input data, the objective functions were defined; the task of the parametric identification according to the results of bench tests through GTE operating modes was performed; analytical approximating dependences for correcting coefficients (variable parameters) were obtained; structural-parametric identification of the mathematical model was performed. The novelty of the obtained results is the identification of the mathematical model of the nonlinear component GTE of the second level performed without model linearization (without its level lowering) by using the Optimum software packages. The methodological approach for the parametric identification of the mathematical model is proposed. This approach allows reducing the number of variable parameters under the modes lower that the maximum. It shows that the identified model allows obtaining the prediction results of the GTE parameters and characteristics through operating modes with a deviation of no more than 1.4% from the experimental data and, therefore, it will allow reduction of terms and an increase in the quality of power unit development.