This paper presents the concept for the development of predictive models of social and economic system evolution providing the necessity of combining solution search optimization algorithms and methods of regressive and clustering analysis for the adequate description of system attribute space. The rationale for the selection of metrics on the basis of a dynamic time-warping algorithm which allows to carry out clustering of the system attribute space. The example of solution of description task for COVID-19 pandemic development attribute for a particular country or region is considered. The developed concept formulates main provisions and indicators that can be used in order to increase the algorithm efficiency for the development of predictive complicated system models. © The Authors, published by EDP Sciences, 2020.