Fluorinated molecules such as perfluoroalkanes (PFA), perfluoroalkylalkanes (PFAA), fluoroalkanes, and hydrofluoroethers (HFE) possess attractive physical properties that have resulted in their use in a wide range of applications. However, while there is an abundance of thermophysical data for hydrocarbons in the literature, only limited studies have been performed that report the properties of the corresponding fluorinated species. Predictive approaches are therefore needed to accurately and reliably determine the physical properties of these molecules. The statistical associating fluid theory (SAFT) is a commonly used molecular-based equation of state that in its various forms has been applied to study a wide range of fluid systems. In recent work, several group contribution (GC) SAFT equations of state have been proposed, such as the GC-SAFT-VR equation that combines the SAFT equation for potentials of variable range (VR) with a group contribution approach that uniquely allows for the description of hetero-segmented chains. The GC-SAFT-VR equation has been shown to provide an excellent description of the phase behavior of pure associating and non-associating fluids and their mixtures, with a minimal reliance on fitting the model parameters to experimental data. Specifically, parameters for key functional groups (such as CH3, CH2, CH, CH2=CH, C=O, C6H5, ether and ester, OH, NH2, CH=O, COOH) have been obtained by fitting to experimental vapor pressure and saturated liquid density data for selected low molecular weight fluids and then used to predict the phase behavior of pure fluids and their mixtures without further adjusting the group parameters. To expand upon this effort, here we report parameters for the CF3, CF2, CF, CH2F, CHF2, and CHF functional groups and their cross interactions. The theoretical predictions are compared with experimental data for pure PFAs, PFAAs, and HFEs, as well as binary mixtures of alkanes, alkenes, PFAs, PFAAs, and CO2 in order to test the transferability of the new group parameters. The GC-SAFT-VR approach is found to accurately predict the phase behavior of the systems studied. (C) 2017 Elsevier B.V. All rights reserved.