The study is devoted to the problem of the spatial differentiation of population income in Russia's regions. The objective of the study is the development of a system-dynamic model for the calculation of spatial differentiation trajectories of income parameters due to various scenarios. Regional features of the human capital development level influencing the spatial differentiation of population income in the Russian regions are assumed. The formulation of the mathematical problem is based on the results of regression analysis of the influence of time series values of socio-demographic factors on population incomes differentiation (Gini coefficient). A specialist application, PowerSim Studio Express 10, was used for model design. Rosstat data on households in the Russian regions were used for calculation of the model experimental trajectories. The main research methods are the following: dynamic analysis of time series; econometric and system-dynamic modeling. As a result of the study, a system-dynamics experimental model was proposed. It was tested in application to eight regions with the most reliable statistical relationship between socio-demographic factors and the Gini index. Numerical experiments were used to simulate real economic processes of convergence and divergence in order to identify the main trends and features of territorial income differentiation depending on local priorities of vocational education development. It was shown that an increase in the level of education, both higher professional and secondary vocational, mainly leads to increased income differentiation. The theoretical significance of the results obtained lies in the deepening of the understanding of the regional features of human capital development influencing the spatial differentiation of population income. The practical significance of the study lies in the expansion of instrumental support for decision-making in the implementation of state policy in the field of regulating the population incomes differentiation at the regional level.