Purpose: The purpose of this experiment was to assess the ability of an acoustic model composed of both time-based and spectral-based measures to track change following voice disorder treatment and to serve as a possible treatment outcomes measure. Method: A weighted, four-factor acoustic algorithm consisting of shimmer, pitch sigma, the ratio of low-to-high frequency spectral energy, and a measure of the cepstral peak was used to predict dysphonia severity in pre- and post-treatment vowel samples from 88 women with primary muscle tension dysphonia treated by manual circumlaryngeal therapy. Predicted severity ratings were also compared to mean perceived severity ratings determined by a group of judges. Results: Predicted severity scores were strongly associated with perceived dysphonia severity ratings for pretreatment, posttreatment, and change in dysphonia severity. Analyses of the agreement between predicted and perceptual severity ratings indicated that the majority of differences were within plus or minus 1 standard deviation from the mean difference. Acoustic predictions of perceived severity were observed to be most accurate for the midportion of the 7-point equal-appearing interval severity scale. Conclusion: The acoustic model and predicted dysphonia severity scores show promise as a sensitive and objective outcomes measure, even with extremely perturbed pre-treatment voice samples that would be difficult to analyze using traditional time-based perturbation measures.