Knowledge of random or structured packings’ hydraulic- and mass transfer performance is crucial for column design. Hydraulic characteristics such as pressure drop (∆P/H), fractional liquid holdup (h_L) and flooding point (F_fl) can be used to determine a column's diameter and are usually experimentally measured with an air-water system. Mass transfer parameters like effective interfacial area (a_eff) and volumetric mass transfer coefficients (ka_eff) provide information about separation performance and can be measured with standardized absorption systems. A column’s packed section height can be calculated from these parameters. Simulations are an alternative way for predicting hydraulic- and mass transfer parameters, which have the advantage of saving time and resources over conducting experiments. Empirical correlations are generally the basis for simulations and many such correlations have been proposed in the past. A commercial simulation software that includes data of many random and structured packings, as well as a variety of correlations for predicting the parameters mentioned above is Aspen Plus. In this work, prediction accuracy of 17 correlations is evaluated by comparing simulation results to literature data for 44 different random and structured packings. Additionally, user-specified packings and correlations can be added to the software. In this work, the Mackowiak correlation for pressure drop and liquid holdup is added to Aspen Plus as a user-subroutine. This correlation requires relatively little experimental data to apply it to a great variety of packings and therefore possesses a significant advantage over other correlations currently included in the software. Furthermore, two packings (RMSR 50-4 and Hiflow 50-6), not previously included in the software, are added into the packings database. Results of pressure drop and flooding point simulations show that overall the “Wallis” correlation performs best for considered packings, which are already included in Aspen Plus. The Mackowiak correlation achieves the best results for the two user-specified packings. The “Mod. Tsai” correlation exhibits good prediction accuracy for effective interfacial area. No correlation for predicting k_G a_eff consistently performs well, however, relevant data is limited in this work. Overall, simulation results are not accurate enough to exclusively rely on them for dimensioning columns.