Binary interaction parameters (BIP) provide a tuning mechanism for various cubic equations of state (CEoS) used in process simulators. BIPs work best when they are obtained through the rigorous regression of experimental data. However, in many important applications experimental data is not available, at least in the initial stages of a project. This work demonstrates the use of the predictive Peng-Robinson CEoS as a generator of BIPs for other CEoS. We show the efficacy of this approach when applied to variations of the well-known Soave-Redlich-Kwong and Peng-Robinson CEoS. We illustrate the utility of this approach by comparing predicted phase equilibrium behavior of various test systems with the corresponding experimental data. The comparisons also include the case where BIPs are set to zero (when no experimental data is available). The results clearly indicate that generated BIPs represent experimental data much better than in the case where BIPs are missing. The composite list of test components consists of carbon dioxide, cumene, ethane, methane, water, n-decane, n-hexadecane, n-nonane, n-octadecane, n-octane, and n-triacontane. The methodology for handling the petroleum fraction is described, and we have a working implementation; the lack of readily available experimental data, however, prevents us from publishing suitable comparisons.