Using a large heterogeneous data-set of 640 organic chemicals, we have developed predictive Quantitative Structure-Activity Relationship models for fish bioconcentration factor (BCF). For 539 chemicals with a log Kow (octanol-water partition coefficient) range of -2.3 to 6.0, we developed a model with r2 = 0.664 and a standard error of 0.661; the primary descriptor was log Kow, and others were polarisability, number of amino groups, hydrogen bond acceptor ability and a molecular shape factor. For 101 chemicals with a log Kow range of 6.0-12.7, we developed a model with r2 = 0.710 and a standard error of 0.777; the descriptors were aqueous solubility (reflecting the importance of this property in governing uptake from aqueous solution), polarity, polarisability, hydrogen bond donor ability and molecular size. Bearing in mind the very great range of BCF values of highly hydrophobic chemicals, our model offers good predictivity of this important environmental property.