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Understanding the evolution of massive binary stars requires accurateestimates of their masses. This understanding is critically important becausemassive star evolution can potentially lead to gravitational wave sources suchas binary black holes or neutron stars. For Wolf-Rayet stars with opticallythick stellar winds, their masses can only be determined with accurateinclination angle estimates from binary systems which have spectroscopic $M\sin i$ measurements. Orbitally-phased polarization signals can encode theinclination angle of binary systems, where the Wolf-Rayet winds act asscattering regions.  We investigated four Wolf-Rayet + O star binary systems, WR 42, WR 79, WR127, and WR 153, with publicly available phased polarization data to estimatetheir masses. To avoid the biases present in analytic models of polarizationwhile retaining computational expediency, we used a Monte Carlo radiativetransfer model accurately emulated by a neural network. We used the emulatedmodel to investigate the posterior distribution of parameters of our foursystems. Our mass estimates calculated from the estimated inclination anglesput strong constraints on existing mass estimates for three of the systems, anddisagrees with the existing mass estimates for WR 153. We recommend a concertedeffort to obtain polarization observations that can be used to estimate themasses of Wolf-Rayet binary systems and increase our understanding of theirevolutionary paths.

New mass estimates for massive binary systems: a probabilistic approach using polarimetric radiative transfer