The aim of this paper is to describe the development and use of a computer simulation model that can be used as a Decision Support System (DSS) to tackle the critical public health issues of the chronic diseases, HIV and HIV related Tuberculosis in the Russian Federation. The model was developed to enable health officials and decision makers to determine the impact of policies to control the chronic diseases spread in an area of Russia. This area, like many others in Russia and elsewhere, have recently witnessed an explosion of HIV infections and a worrying spread of the Multi Drug Resistant form of Tuberculosis (MDRTB). The conclusions drawn is that a high population coverage with Highly Active Anti Retroviral Treatment (HAART) (75% or higher), allied with high MDRTB cure rates, reduces cumulative deaths by 60%, with limited impact below this level. The contributions that this research offers are the development of a simulation model that can be applied as a DSS by public health officials and managers in order to inform policy making. By doing so, ways of best controlling the spread of HIV and MDRTB and reduce the mortality rate from these serious public health threats is provided.