The Regional Haze Rule of the US Environmental Protection Agency mandates reduction in US anthropogenic emissions to achieve linear improvement of visibility in wilderness areas over the 2004-18 period toward an endpoint of natural visibility conditions by 2064. Linear improvement is to apply to the mean visibility degradation on the statistically 20% worst days, measured as a Haze Index in units of deciviews (log of aerosol extinction). We use a global chemical transport model (GEOS-Chem) with 11 Â 11 horizontal resolution to simulate present-day visibility statistics in the USA, compare them to observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) surface network, and provide natural and background visibility statistics for application of the Regional Haze Rule. Background is defined by suppression of US anthropogenic emissions but allowance for present-day foreign emissions and associated import of pollution. Our model is highly successful at reproducing the observed variability of visibility statistics for present-day conditions, including the low tail of the frequency distribution that is most representative of natural or background conditions. We find considerable spatial and temporal variability in natural visibility over the USA, especially due to fires in the west. A major uncertainty in estimating natural visibility is the sensitivity of biogenic organic aerosol formation to the availability of preexisting anthropogenic aerosol. Background visibility is more variable than natural visibility and the 20% worst days show large contributions from Canadian and Mexican pollution. Asian pollution, while degrading mean background visibility, is relatively less important on the worst days. Recognizing the influence of uncontrollable transboundary pollution in the Regional Haze Rule would substantially decrease the schedule of emission reductions required in the 2004-18 implementation phase. Meaningful application of the Rule in the future will require projections of future trends in foreign anthropogenic emissions, wildfire frequency, and climate variables. r