Background and Objectives: The natural history of Friedreich Ataxia (FA) is being investigated in a multi-center longitudinal study designated as the Friedreich Ataxia Clinical Outcome Measures Study (FA-COMS). To understand the utility of this natural history dataset in analysis of clinical trials, we performed a propensity-matched comparison of the data from the open-label MOXIe Extension (omaveloxolone) with that from FA-COMS. Methods: All MOXIe Extension patients who had at least one post-baseline assessment were matched to FA-COMS patients using logistic regression to estimate propensity scores based on multiple covariates: sex, baseline age, age of FA onset, baseline modified Friedreich Ataxia Rating scale (mFARS) score, and baseline gait score. Selection of covariates was based on clinical relevance (i.e., factors considered prognostic for disease progression) and availability. The change from baseline in mFARS at Year 3 for the MOXIe Extension patients compared to the matched FA-COMS patients was analyzed as the primary efficacy endpoint using mixed model repeated measures analysis. Results: Data from the MOXIe Extension show that omaveloxolone provided persistent benefit over three years when compared to an untreated, rigorously matched cohort from FA-COMS. At each year, and in all analysis populations, patients in the MOXIe Extension experienced a smaller change from baseline in mFARS score than the matched FA-COMS patients. In the Primary Pooled Population (136 patients in each group) by Year 3, patients in the FA-COMS matched set progressed 6.6 points whereas patients treated with omaveloxolone in MOXIe Extension progressed 3 points (difference = -3.6; nominal p value = 0.0001). Thus, progression in mFARS was slowed by 55% with omaveloxolone treatment relative to the patients in the FA-COMS data set. Conclusions: These results suggest a clinically meaningful slowing of FA progression with omaveloxolone, and consequently detail how propensity-matched analysis may contribute to the understanding of the effects of therapeutic agents. This supports the potential value of the FA-COMS dataset in the evaluation of FA clinical trials.