A bioconcentration factor (BCF) estimation model for a wide range of nonionic organic compounds was developed on the basis of molecular connectivity indices and polarity correction factors. The nonlinear topological modeling using polarity correction factors resulted in the best BCF estimation quality for all of the 239 compounds studied, with a mean absolute estimation error of 0.478 log units. Residual analysis indicated that the estimation errors came from many sources including BCF measurement, test species, and selection of descriptors. Statistical robustness of the developed model was validated by modified jackknifed tests where random deletion of a set of compounds and specific deletion of a class of compounds were both performed. Comparison between the MCI-based (molecular connectivity indices) model and a Kow-based (octanol/water partition coefficient) model revealed that the BCF estimation based on topological parameters was as good as that achieved by Kow.