Stable isotope analysis is regularly used in order to acquire detailed information of physical and chemical processes that a system is undergoing. Experimental data is thus complemented with computational studies, in order to develop theoretical models that can satisfactorily explain and predict a determined phenomenon in similar systems. However, proper estimation of isotope effects remains a challenging task. High levels of theory are demanded in order to correctly describe non-covalent interactions, while large molecular systems are required to mimic solvent effects. Given specifications typically restrict the available theoretical approach to a few electronic structure methods.In this study equilibrium isotope effects (EIEs) on evaporation to several organic solvents (bromobenzene, dibromomethane, ethanol, methanol, and trichloromethane) in the pure phase are estimated employing Kohn-Sham Density functional theory (KS-DFT) along with full Hessian vibrational analysis (FHVA) and partial Hessian vibrational analysis (PHVA). Both FHVA and PHVA qualitatively predict compounds EIEs.Weakly interacting systems (bromobenzene, dibromomethane, and trichloromethane) display identical EIE values for both, FHVA and PHVA. Whereas for strongly interacting systems (ethanol and methanol), PHVA estimates slightly smaller EIE compared to FHVA. By employing the symmetry-adapted perturbation theory (SAPT) along with independent gradient model (IGM), it was possible to establish how minimal changes in compounds interaction energy affected carbon and bromine EIEs estimation in dibromomethane. Moreover, SAPT and IGM revealed how in ethanol, apparently insignificant intermolecular interactions possessed an enormous impact in carbon position specific isotope effects, which highlight the importance of solvent effects for strongly interacting compounds. The presented results have important implications for correctly comprehending and characterising the role of non-covalent interactions in the prediction of isotope effects, as well as providing a robust test to PHVA for the prediction of EIEs.