A statistical procedure to evaluate melanoma risk in Caucasian subjects on the basis of colorimetric measurement of skin colour and Fitzpatrick phototype is described. One hundred and sixty melanoma patients and 546 randomized healthy subjects of similar age, sex and place of origin were examined in the same period for skin colour using a tristimulus colorimeter and for Fitzpatrick phototype. A clinical score for classification purposes was obtained by statistical discriminant analysis with multivariate data transformation and dimension reduction techniques. A Fisher linear classifier was chosen for its simplicity and robustness in correctly predicting melanoma risk in new subjects. The classification rule was designed to avoid classifying subjects at high risk for melanoma as low risk, i.e. to give a negligible number of false negatives at the expense of more false positives. The procedure is objective and readily adapted to different clinical requirements. This is only a preliminary study but it is hoped that by performing more complex statistical analyses, e.g. neural networks, and adding other parameters (proven risk factors such as number of naevi) the performance will be further improved.