Tissue:plasma (P(t:p)) partition coefficients (PCs) are important parameters describing tissue distribution of drugs. The ultimate goal in early drug discovery is to develop and validate in silico methods for predicting a priori the P(t:p) for each new drug candidate. In this context, tissue composition-based equations have recently been developed and validated for predicting a priori the non-adipose and adipose P(t:p) for neutral organic solvents and pollutants. For ionizable drugs that bind to different degrees to common plasma proteins, only their non-adipose P(t:p) values have been predicted with these equations. The only compound-dependent input parameters for these equations are the lipophilicity parameter, such as olive oil-water PC (K(vo:w)) or n-octanol-water PC (P(o:w)), and/or unbound fraction in plasma (fu(p)) determined under in vitro conditions. Tissue composition-based equations could potentially also be used to predict adipose tissue-plasma PCs (P(at:p)) for ionized drugs. The main objective of the present study was to modify these equations for predicting in vivo P(at:p) (white fat) for 14 structurally unrelated ionized drugs that bind substantially to plasma macromolecules in rats, rabbits, or humans. The second objective was to verify whether K(vo:w) or P(o:w) provides more accurate predictions of in vivo P(at:p) (i.e., to verify whether olive oil or n-octanol is the better surrogate for lipids in adipose tissue). The second objective was supported by comparing in vitro data on P(at:p) with those on olive oil-plasma PC (K(vo:p)) for five drugs. Furthermore, in vivo P(at:p) was not only predicted from K(vo:w) and P(o:w) of the non-ionized species, but also from K*(vo:w) and P*(o:w), taking into account the ionized species in addition. The P(at:p) predicted from K*(vo:w), P*(o:w), and P(o:w) differ from the in vivo P(at:p) by an average factor of 1.17 (SD = 0.44, r = 0.95), 15.0 (SD = 15.7, r = 0.59), and 40.7 (SD = 57.2, r = 0.33), respectively. The in vitro values of K(vo:p) differ from those of P(at:p) by an average factor of 0.86 (SD = 0.16, r = 0.99, n = 5). The results demonstrate that (i) the equation using only data on fu(p) as input and olive oil as lipophilicity surrogate is able to provide accurate predictions of in vivo P(at:p), and (ii) olive oil is a better surrogate of the adipose tissue lipids than n-octanol. The present study is an innovative method for predicting in vivo fat partitioning of drugs in mammals.