Introduction. Organisations’ performance evaluation results have now become an important management resource. Therefore, it is not only compliance with the targets set by the founder that is relevant for the organisation, but also inclusion in the TOP prestigious ratings list, both of general nature and set for a particular activity. The purpose of the research is designing the research performance forecasts for universities and ratings on their basis by simulation modelling methods, as well as the formation of managerial decisions aimed to promote a specific university in the rating list. Materials and methods. The research materials are represented by the data on the number of university staff publications in the leading scientometric databases Web of Science, Scopus, RSCI, and the numbers of academic staff (research and teaching staff) in the period from 2013 to 2021. The methods of mathematical and simulation modelling, as well as the methods of descriptive statistics and comparative analysis of data were used in the research. Results. The dynamics of scientific activity indicators for TOP-50 universities until 2030 was modelled within the framework of studying the methodology for the formation of a specific well-known national rating of Russian universities, on the basis of sixteen universities from the above. The managerial decisions projects allowing a university which is not included in the TOP-50 to get into this list, with regard for minimisation of financial expenses, are proposed by the example of Petrozavodsk State University. It is proposed to implement the said management decision projects through involvement in publication activities of the university academic staff that has not had any annual publications within several preceding years. Following the simulation modelling of projected values of scientific performance indicators, it was revealed that in case of annual increase in the number of publications by 25% on the average, Petrozavodsk State University can essentially improve its positions in the rating of scientific activity and take a position in a range between 40 and 50 by 2025. Discussion and conclusion. The obtained models make it possible to prognosticate not only the total number of articles at particular Russian universities, but also their positions in the rating, both in case of preservation of current tendencies and realisation of different management scenarios. From the practical point of view, the presented results can be useful for the university administration in terms of analysis and management of the scientific work at the university, with the view to improve the academic performance and achieve the set goals.