This study aims to develop a valuation model for lab-grown cut diamonds based on data published on the Internet. Regression trees, Bayesian Networks, and K-Nearest Neighbors are used for this purpose. These different techniques have a complementary role in the application. The K-Nearest Neighbors has a better performance in prediction. Regression trees contribute to a better understanding of the relationship between predictors and the target. Bayesian Networks also add some insights in this respect. Finally, the models’ results are compared to similar approaches when applied to natural diamonds.

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Lab-grown diamonds,Price,Regression Trees,K-Nearest Neighbors,Bayesian Networks