As a result of poor fluid delivery in tight oil reservoirs, oil production drops rapidly at early stages of depletion development. While water flooding only boosts production to a limited extent, CO2 miscible flooding seems a promising technique in improving tight oil recovery. Generally, CO2 flooding is performed only after water flooding gives better results than natural depletion. Since cumulative CO2 injection versus oil production goes up as formation permeability goes down, it is crucial to select suitable reservoir candidates to conduct CO2 flooding to be economically successful. There are several methods of ranking candidate reservoirs for the CO2 enahnced oil recovery (EOR) process based on criteria on reservoir parameters. Nevertheless, few of them take account of an oil recovery increment and risk analysis. In this paper, an integrated method for CO2 flooding reservoir screening criteria is presented, considering asphaltene precipitation and an oil recovery factor increment. This method is based on the least squares method, reservoir simulation, and fuzzy analytical hierarchy process, associated with equation of state (EOS) compositional calculations and compositional modelling. It is applicable in high diversity and can be used as guidance to screen tight oil reservoirs for CO2 flooding.