Digital dermoscopy analysis (DDA) exploits computerized analysis of digital images and offers the possibility of parametric analysis of morphological aspects of pigmented skin lesions by means of integration with dedicated software. We conducted a study by DDA in 141 melanomas, with the aim assessing whether the numerical variables extrapolated by univariate logistic analysis could be used in a system of multivariate analysis to predict melanoma thickness before surgery. Melanoma images were evaluated for 49 DDA parameters. Logistic analysis was conducted to identify statistically significant variables. The leave-one-out method was used to evaluate the predictive representations of rules for stepwise logistic classification. The percentage of correctly classified cases was calculated by a classification matrix. Melanomas less than 1 mm had a smaller area, faded borders and were more symmetrical than melanomas greater than 1 mm. The latter had a bluer colour and more random disposition of elements. The accuracy was 86.5%. Specifically, 97 of 108 thin melanomas (specificity 89.8%) and 25 of 33 thick melanomas (sensitivity 75.7%) were correctly classified. In conclusion, the predictive value of DDA for melanoma thickness was quite good. Moreover, DDA allowed us to know objectively those dermoscopic features important in the differentiation between thick and thin melanoma. However, further studies should be performed in a prospective setting before the clinical application.