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This work describes a novel application of a recently developed statistical partial least-squares regression technique for the problem of establishing relationships between experimental variables in crystallization trials and the experimental results. To validate this method published sets of factorially designed crystallization trials were analyzed and it was discovered that these derived models show very good predictivity. These mathematical constructs cannot explain the detailed mechanism of crystallization, but are a pragmatic and powerful tool which enables the crystal growers to set up crystallization trials not only in a rational manner but also with confidence. This is a useful and a general methodological approach particularly when crystallizing proteins of limited supply.