Pulmonary fibrosis contributes to morbidity and mortality in a range of diseases, and there are no approved therapies for reversing its progression. To understand the mechanisms underlying pulmonary fibrosis and assess potential therapies, mouse models are central to basic and translational research. Unfortunately, metrics commonly used to assess murine pulmonary fibrosis require animals to be grouped and sacrificed, increasing experimental difficulty and cost. We examined the ability of three magnetic resonance imaging (MRI)-derived metrics (mean weighted lung signal, percent high signal volume, and signal coefficient of variation) to non-invasively assess lung fibrosis progression and resolution in a doxycycline (Dox) regulatable, transgenic mouse model that overexpresses transforming growth factor alpha (TGF-α) under control of a lung-epithelial-specific promoter. During seven weeks of Dox-treatment, fibrotic lesions were readily observed as high-signal tissue. Mean weighted signal and percent signal volume were found to be the most robust MRI-derived measures of fibrosis, and these metrics correlated significantly with pleural thickness, histology scores, and hydroxyproline content (R=0.75-0.89). When applied longitudinally, percent high signal volume increased by 1.5% week^-1 (p<0.001), and mean weighted signal increased at a rate of 0.0065 week^-1 (p=0.0062). Following Dox-treatment, lesions partially resolved, with percent high signal volume decreasing by -3.2% week^-1 (p=0.0034) and weighted mean signal decreasing at -0.015 week^-1 (p=0.0028). Additionally, longitudinal MRI revealed dynamic remodeling in a subset of lesions-a previously unobserved behavior in this model. These results demonstrate MRI can non-invasively assess experimental lung fibrosis progression and resolution and provide unique insights into its pathobiology.