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This article contributes to the development of the concept of second-tier cities. In this study, it is proposed to identify second-tier cities based on the performance indicator of creative industries. To do this, the DEA indicator of creative industries is calculated for the full list of cities in Kemerovo, Sverdlovsk, Chelyabinsk, Tomsk Oblasts, Khanty-Mansi Autonomous Okrug, and Altai Krai, and its clustering is carried out using the t-SNE machine learning method (t-distribution stochastic neighbor embedding). The results of the study show a cluster of cities close to administrative centers (unambiguous leaders in key socio-economic indicators) that can take on the role of the core of second-tier cities: Nizhny Tagil, Magnitogorsk, Miass, Novokuznetsk, Biysk, Surgut, Kogalym, Nizhnevartovsk. The analysis of the dynamics of the resulting cluster makes it possible to identify a feature in the development of creative industries in Novokuznetsk, Nizhnevartovsk and Surgut. Comparing the results obtained with the distribution of cities according to the Zipf model (by population, aggregated revenue, fixed assets and wages), the authors conclude that it is possible to allocate second-tier cities based on the performance indicators of creative industries. Thus, this study contributes to the confirmation of the thesis about the importance of the factor of development of creative industries in the conditions of new industrialization.