The crop area of sugar cane production in Brazil has increased substantially in the last few years, especially to meet the global bioethanol demand. Such increasing production should take place not only in new sugar cane crop areas but mainly with the goal of improving the quality of raw material like sugar content (Pol). Hence, models that can describe the behaviour of the quality parameters of sugar cane may be important to understand the effects of the soil attributes on those parameters. The objective of this work was to fit mathematical models to the sugar cane Brix, pol and fiber using the physical chemical soil attributes as predictors. This work was carried out in an area of 10 ha located in Araras/SP, Brazil, during three crop cycles starting from 2008. The chemical soil attributes analyzed were the macro and micronutrients, and the soil physical attribute was the soil texture. The variables used in the models were chosen using stepwise procedure, and the fit of the models was made by means of multiple regressions. We compared the results using kriging to map the Brix and pol with the true and estimated values. The models presented a R2 varying from 0.36 to 0.46 during all two crop cycles for Brix, from 0.15 to 0.47 for pol and from 0.12 to 0.80 for fiber. Those results allowed obtaining a residue between 0.3 e 0.4 as result for the Brix, pol and fibre estimations, representing the third quartile of the estimated data by means of the models throughout the experiment.