PURPOSE: This study uses a voice production model to estimate muscle activation levels and subglottal pressure (P METHOD: The study obtained ambulatory voice data from patients diagnosed with PVH and a matched control group. To infer physiological parameters, ambulatory data were mapped onto synthetic data generated by a physiologically relevant voice production model. Inverse mapping strategies involved selecting model simulations that represented ambulatory distributions using stochastic (random) sampling weighted by probability with which different vowels occur in English. A categorical approach assessed the relationship between different values of DPI and changes in estimated physiological parameters. RESULTS: Results showed significant differences between the PVH and control groups in key parameters, including statistical moments of H CONCLUSIONS: This study demonstrated that noninvasive ambulatory voice data could be used to drive a voice production modeling process, providing valuable insights into underlying physiological parameters associated with PVH. Future research will focus on refining the predictive power of the modeling process and exploring the implications of these findings in further delineating the etiology and pathophysiology of PVH, with the ultimate goal to develop improved methods for the prevention, diagnosis, and treatment of PVH. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.28352720.