To estimate the bioconcentration factor (BCF), the in vitro intrinsic clearance (CLIN VITRO,INT) from rainbow trout liver S9 fractions (RT-S9) can be applied to in vitro–in vivo extrapolation (IVIVE) models, yet uncertainties remain in model parameterization. An alternative model approach is evaluated: a regression model was built in the form log BCF = a × log K ow + b × log CLIN VITRO,INT. The coefficients a and b were fitted based on a training set of 40 chemicals. A high robustness of the coefficients and good accuracy of BCF prediction were found on independent datasets of neutral organic chemicals (measured log K ow 3.3–6.2). BCF predictions were similar to or in better agreement with in vivo BCFs compared to IVIVE models (2.4- to 2.9- vs 2.8- to 3.6-fold misprediction) for training and test sets. Species-matched models (trout, carp) did not result in improvements. This study presents the largest dataset on CLIN VITRO,INT and BCFs to assess predictivity of the RT-S9 assay. The robustness of the regression statistics on different datasets and the high statistical weight of the CLIN VITRO,INT term illustrate the predictive power of the RT-S9 assay as an important step toward regulatory acceptance to replace animal experiments.