The octanol-air partition coefficient (K(OA)) is useful for predicting the partitioning behavior of organic compounds between air and environmental matrices such as soil, vegetation, and aerosol particles. At present, experimentally determined K(OA) values are available for only several hundred compounds. Therefore, the ability to estimate K(OA) is necessary for screening level evaluation of most chemicals. Although it is possible to estimate K(OA) from the octanol-water partition coefficient (K(OW)) and Henry's law constant (HLC), various concerns have been raised in regard to the usability of this estimation methodology. This work examines the accuracy and usability of K(OW) and HLC in application to a comprehensive database set of K(OA) values for screening level environmental assessment. Results indicate that K(OW) and HLC can be used to accurately predict K(OA) even when estimated K(OW) and HLC values are used. For an experimental dataset of 310log K(OA) values for different compounds, the K(OW)-HLC method was statistically accurate as follows: correlation coefficient (r2): 0.972, standard deviation: 0.526, absolute mean error: 0.358 using predominantly experimental K(OW) and HLC values. When K(OW) and HLC values were estimated (using the KOWWIN and HENRYWIN programs), the statistical accuracy was: correlation coefficient (r2): 0.957, standard deviation: 0.668, absolute mean error: 0.479.