The broad aim of this work is to propose different modifications to the Cubic-plus-chain (CPC) equation of state (Sisco et al., Industrial & Engineering Chemistry Research, 2019) to improve modeling predictions and to model short and long-chain associating mixtures. The CPC equation hybridizes the classical cubic EoS with the chain term from the Statistical Associating Fluid Theory (SAFT) to develop an equation capable of modeling short and long-chain components. The CPC EoS is not limited to one classical EoS form, and different cubic forms can be used in the model. CPC-RK (RK reference form) and CPC-SRK (SRK reference form) are applied to model different binary mixtures ranging from alkanes to homopolymers. Different factors such as elevated pressures, polydispersity, molecular weight, and solvent types were analyzed to test the model performance. In addition, an extension is proposed to the CPC model framework to account for copolymers such as poly(ethylene-co-propylene) and poly(ethylene-co-vinyl acetate). Both CPC versions show good homopolymer and copolymer phase equilibria predictions compared with experimental cloud points and PC-SAFT simulation results. CPC-RK and CPC-SRK versions require using temperature-dependent binary interaction parameters (k_ij ). Moreover, those two versions do not predict liquid density accurately. Hence, different modifications are studied to improve the model description. A modified CPC version is proposed by incorporating short-range soft repulsion in the CPC framework, which is called CPC-SRK-b(T). A temperature-dependent function is introduced to the co-volume parameter in the CPC-SRK-b(T) model. CPC-SRK-b(T) overcomes limitations in CPC-RK and CPC-SRK versions by improving liquid density predictions and modeling various binary systems using a constant k_ij value. Simulation parameters database of CPC-SRK-b(T) for more than 50 components is provided. Furthermore, the cubic-plus-chain and association (CPCA) equation of state is proposed to account for short and long-chain associating fluids ranging from water and alkanols to associating polymers. CPCA shows excellent saturation pressure and liquid density predictions of pure associating components. Moreover, different mixtures’ categories including alcohol/alkane, alcohol/alcohol, alcohol/aromatics, alcohol/water, amine/alkane, and associating polymer/solvents are analyzed with CPCA showing good agreement with experimental data.