An abundance of chemical processes in nature occur in solution. Chemical reactions are hugely affected by their solvent environments; for instance, the SN2 displacement occurs most readily in polar aprotic media. It is therefore important to understand and to be able to model the solvent environments in which such processes occur. Computational Polarizable Continuum Models, PCMs, have been developed to help understand chemical processes. The most popular and successful of the PCMs, the SMD (Solvation Model Density) model developed by Cramer and co-authors, helps bridge the gap between experimental and computation methodology. The SMD continuum utilizes bulk electrostatics and cavity-dispersion-solvent-structure terms as parameters to characterize the response of solvent to a solute. We seek to investigate and evaluate the performance of these implicit PCMs. A widely available thermodynamic parameter that defines the difference between gas and liquid phases for many organic compounds is the heat of vaporization. We intend to investigate the various PCMs’ effectiveness at predicting heats of vaporization for common organic solvents such as Acetonitrile, Benzene, Tetrahydrofuran, Cyclohexane, Ethanol, etc. Specific computational methodologies to be surveyed will include DFT and wavefunction methods such as ωB97xD, MP2, and CCSD, and basis sets from the Pople (e.g. 6-31++G**, 6-311++G**, etc.), and Dunning (e.g. aug-ccPVDZ, aug-ccPVQZ) families. By calculating the gas and solution (solvent molecule embedded within the corresponding simulated continuum) phases we can compare these experimental values from the NIST database to assess the performance of Polarizable Continuum Models.