In this study, structure water solubility modeling was performed to describe a set of 50 of aliphatic alcohols in a Quantitative Structure-Property Relationship model by developing two descriptors types based on multifunctional autocorrelation method and electro-topological descriptors. The Modified Autocorrelation Method was used to describe the local environment of the hydroxyl group. Multiple Linear Regression, Artificial Neural Networks and Principal Components Analysis were analyzed the alcohols series. The efficiency approach was evaluated through the predictive ability of models by leave-p-Out cross-validation method. The molecules were coded by means of SMILES system and stored as input files. The results showed that aliphatic alcohols solubility is dominated by the shape and molecule branching, also the electro-topological descriptors had a considered model effect.