This paper describes a graphical model for simplifying in vitro absorption, metabolism, distribution, and elimination (ADME) data analysis through the estimation of oral bioavailability (%F) of drugs in humans and other species. This model integrates existing in vitro ADME data, such as Caco-2 permeability (P(app)) and metabolic stability (percent remaining - %R) in liver S9 or microsomes, to estimate %F into groups of low, medium, or high regions. To test the predictive accuracy of our model, we examined 21 drugs and drug candidates with a wide range of oral bioavailability values, which represent approximately 10 different therapeutic areas in humans, rats, dogs, and guinea pigs. In vitro data from model compounds were used to define the boundaries of the low, medium, and high regions of the %F estimation plot. On the basis of the in vitro data, warfarin (93%), indomethacin (98%), timolol (50%), and carbamazepine (70%) were assigned to the high %F region; propranolol (26%) and metoprolol (38%) to medium %F region; and verapamil (22%) and mannitol (18%) to the low %F region. Similarly, the %F of 11 drug candidates from Elastase Inhibitor, NK1/NK2 antagonist, and anti-viral projects in rats, guinea pigs, and dogs were correctly estimated. This model estimates the oral bioavailability ranges of neutral, polar, esters, acidic, and basic drugs in all species. For a large number of drug candidates, this graphical model provides a tool to estimate human oral bioavailability from in vitro ADME data. When combined with the high throughput in vitro ADME screening process, it has the potential to significantly accelerate the processes of lead identification and optimization.