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Purpose: To determine the association between diabetic retinopathy (DR) severity and quantitative retinal vascular features. Design: Retrospective image analysis study. Participants: Eyes with DR and eyes with no posterior segment disease (normal eyes) that had undergone ultra-widefield fluorescein angiography (UWFA) with associated color fundus photography. Exclusion criteria were any previous laser photocoagulation, low image quality, intravitreal or periocular pharmacotherapy within 6 months of imaging, and any other significant retinal disease including posterior uveitis, retinal vein occlusion, and choroidal neovascularization. Methods: The centered early mid-phase UWFA frame that captured the maximum vessel area was selected using automated custom software for each eye. Panretinal and zonal vascular features were extracted using a machine learning algorithm. Eyes with DR were graded for DR severity as mild nonproliferative DR (NPDR), moderate NPDR, severe NPDR, and proliferative DR (PDR). Parameters of normal eyes were compared with age- and gender-matched patients with DR using the t test. Differences between severity groups were evaluated by the analysis of variance and Kruskal-Wallis tests, generalized linear mixed-effects models, and random forest regression models. Main Outcome Measures: Diabetic retinopathy severity and vascular features (panretinal and zonal vessel area, length and geodesic distance, panretinal area index, tortuosity measures, vascular density measures, and zero vessel density rate). Results: Ninety-seven eyes from 60 patients with DR and 12 normal eyes from 12 patients that underwent UWFA for evaluation of fellow eye pathology had images of sufficient quality to be included in this analysis. The mean age was 60 ± 10 years in DR eyes and 46 ± 17 years in normal eyes. Panretinal vessel area, mean geodesic distance, skewness, and kurtosis of local vessel density was significantly higher in normal eyes compared with the age- and gender-matched eyes with DR (P < 0.05). Zero vessel density rate, skewness of vessel density, and mean mid-peripheral geodesic distance were among the most important features for distinguishing mild NPDR from advanced forms of DR and PDR versus eyes without PDR. Conclusions: Automated analysis of retinal vasculature demonstrated associations with DR severity and visual and subvisual vascular biomarkers. Further studies are needed to evaluate the clinical significance of these parameters for DR prognosis and therapeutic response.