Abstract: Stochastic-based descriptors generated by the MARCH-INSIDE methodology are applied to the prediction of several properties related to electronic, hydrophobicity and size dependent parameters. Linear Regression is the statistical technique employed finding these quantitative correlations. The model obtained explained more than the 85% of the experimental variance and are comparable in the quality of their statistical parameters and predictive power with those previously reported for the prediction of isoelectric point but using robust methodologies for variable selection like Genetic Algorithm and Partial Least Squared (PLS) as well as neural network for the quantitative correlation.