In this work, we develop and validate coarse-grained (CG) models for simulating the intrinsic thermophysical properties of polyvinyl chloride (PVC) and dehydrochlorinated PVC (DHPVC). The CG models are generated by using fuzzy self-tuning particle swarm optimization and iterative Boltzmann inversion, and they provide results consistent with the all-atom PVC model and with available experimental data. Several properties are evaluated within different solvents-acetone, ethyl acetate, water, and tetrahydrofuran-including bond lengths, angles, dihedral distributions, radius of gyration (R-g), end-to-end distance (R), radial distribution functions (RDFs), surface area, and potential of mean force. Additionally, CG models are validated by benchmarking mechanical properties in melt (MELT) systems, such as the stress-strain relationship and glass transition temperature. The CG model for DHPVC reliably predicts the physical changes observed after dehydrochlorination in ETA and MELT, by accurately depicting changes in dihedral distributions, polymer chain planarity, R-g, R, RDF variations, and the consequential reduction in melt viscosity. These validated CG models enable computationally efficient simulations of PVC and DHPVC interactions in various solvents and melts.