In the article we propose new decision support tools for region energetics development. The method is based on analysing complex system’s state and comparing it with the self-organized criticality (SOC) class that characterize the long-term system’s stability. We start with urban system modelling using cellular automata (CA) with the best fit to real data and then we raise hypothesis about adequacy of urban and energetics system elements distribution. The urban data analysis shows that it is in SOC state for wide rank of countries. We calculate required parameters for energetics system, which are used in decision making for the system long-term development.