Introduction: Various caries risk prediction models have been developed in recent years. Cariogram®, a software program that evaluates an individual?s caries risk profile and illustrates it in graphic form, appears to classify patients more correctly than other risk prediction methods. Objectives: The objective of this study was to determine the caries risk of a population by means of the Cariogram® software and examine the relationships between the different variables used by the Cariogram® and the risk of caries determined by this program. Materials and Methods: Data were collected from a sample of 48 young individuals by clinical and radiological examination, saliva sampling and a dietary questionnaire. The caries risk of each individual was then obtained by drawing up the Cariogram®. Results: Past caries experience, Streptococcus mutans counts, Fluoridation programme and Buffer capacity of the saliva are the factors included in the Cariogram that showed significant correlation with the caries risk determined by the program. Other factors that the Cariogram® does not include directly, such as DMFT, DMFS and the plaque index, also showed high correlation with risk. Conclusions: Linear regression analysis makes it possible to draw up more simplified models from the predictive variables with the highest correlation to caries risk. The predictive variable which makes the greatest contribution to the model is Streptococcus mutans count, followed by the DMFT index and the Buffer capacity of the saliva.