Experimental determination of logP values can be achieved by various techniques such as shake flask 6 , chromatography 7 , among others. Theoretical estimation of logP values is a common practice to predict the solubility of a molecule during the design phase because it saves valuable materials and reduces time-consuming procedures by targeting compounds with desired solubilities and disregarding those without them. This costeffective strategy has a significant contribution to the synthesis and development of potential drug candidates. However, the application of the theoretical estimation of logP values is limited to its correlation with the logP values obtained experimentally. The most common method for calculating logP values is with software based on the quantitative structure property relationships (QSPR) model. Nevertheless, the estimated value using the QSPR model has a poor correlation with the experimental logP value because it is limited to a database of experimental logP values of similar molecules. For that reason, computational physics-based free energy models where the solvent is included implicitly with a continuum solvent model are preferred. Recently, Nedyalkova et al. used Density Functional Theory (DFT) to predict the noctanol/water logP values of 55 organic molecules. They reported the best correlations with the experimental data using the functionals M11 and M06-2X. In this work, we have expanded the list of compounds to a total of 161 molecules by adding 106 molecules from Spafiu et al. to the test set used by Nedyalkova et al. We proceeded to performed calculations with DFT, semiempirical and molecular mechanics (MM) computational methods to benchmark these methodologies. We found the best correlation to be obtained with wB97XD/6-311+G(2d,p).