This framework applies well to situations where the presence of a few molecules (e.g. as catalysts) dramatically affects the local processing fate of the system. This is usually the case inevolving chemical or biological systems. PRESS is an acronym forProbability Reduced Evolution of Spatially Discrete Species. The PRESS platform extends stochastic chemical system dynamics to the spatial domain, making use of a self-consistent probabilty field theoretical framework. The master equations for the time evolution of the probabilities of local occupation of a site with discrete numbers of chemicals arecoupled self-consistentlyto the probability dynamics on other sites. The formulation admits an analytic treatment of stationary solutions and efficient integration of dynamicsvia coupled ODEsin the general case. It has been tested against Monte Carlo simulations of the full spatial systems in 2D and 3D forvarious catalytic chemical processes.