his work has solved a relevant task to ensure the required level of quality of experience in an infocommunication network, which implied the development of a mathematical model of the multipath QoE-routing while maintaining the required quality rating. In this case, quality rating calculation requires the introduction to the mathematical model of routing of additional conditions for obtaining the indicators of an end-to-end delay and a packet loss probability. To this end, it is advisable to use the tensor formalization of these conditions when implementing a multipath routing strategy. Such a technique for expanding the mathematical models (introduction of additional analytical conditions) is more flexible and would full account for the complexity of relationship between network parameters within QoE. Given this, the quality of experience of speech transmission is not defined by the absolute values of delays and loss probabilities, but rather by their relationship. The result of studying the proposed model is the calculated quantitative indicator for a quality rating, which, compared to recommended indicators according to existing recommendations, makes it possible to evaluate the execution of the predefined level of QoE. In other words, given the preset intensity of traffic in a network, we calculated indicators for the average end-to-end delay and a packet loss probability, which make it possible to assess the quality of experience in terms of a quality rating and indicate the efficiency of the proposed solution. And, on the contrary, owing to the developed model of QoE-routing, it has become possible to control the probability of losses and the average end-to-end packet delay in an infocommunication network in order to ensure meeting the specified QoE-requirements. In addition, a comparative analysis was performed of a flow model of multipath routing based on using the IGRP metric, which made it possible to assess the effectiveness of the proposed solution and demonstrated better performance in terms of a quality rating by 12 to 25 % depending on the source data.