In this work, novel techniques for predicting vapor pressure and binary interaction coefficients for homologous series are developed based on the previously proposed targeted quantitative structure-property relationship (TQSPR) and QS2PR methods. For predicting vapor pressure variation as a function of temperature, a two-reference compound (TRC) QSPR method is suggested. This method uses two, structurally similar predictive compounds with available vapor pressure data to predict point by point the vapor pressure or the saturation temperature of a target compound. For the target compound, only structural information is required. The two variants of the method were applied to several homologous series. They demonstrate prediction of vapor pressure within experimental uncertainty, depending on the level of similarity between the predictive compounds and the target compound. A targeted QSPR method for prediction of the binary interaction coefficients (kij) in cubic equations of state for a compound with the members of its homologous series is also presented. The coefficients for the Soave-Redlich-Kwong and Peng-Robinson equations, used to test the method, were reproduced within the deviation of those obtained from regressed experimental data.