Background: Recent food-based recommendations for flavan-3-ols highlight a growing need to understand the breadth of our dietary polyphenol exposure. However, estimation of dietary polyphenol intake remains challenging, requiring custom computational tools that are often difficult to implement or not fully reproducible. Objective: We aimed to an automated, user-friendly tool to estimate polyphenol intake from diet recalls and records. Methods: We developed Polyphenol Estimator, a tool that processes dietary data from the Automated Self-Administered 24-Hour (ASA24) Dietary Assessment Tool or the Automated Multiple-Pass Method from the National Health and Examination Survey (NHANES). Polyphenol Estimator disaggregates foods using the FDA Food Disaggregation Database into ingredients, matches these ingredients to FooDB, and estimates polyphenol intake at the total, class, and compound level. Optionally, these polyphenol estimates can be used to calculate the Dietary Inflammatory Index (DII). Polyphenol Estimator is freely available online (https://swi1.github.io/polyphenol_estimator) with a tutorial for users with limited programming experience. Results: To illustrate Polyphenol Estimator, we applied it to two days of diet recalls from adults ([≥] 20 years) in NHANES 2021-2023 (n = 2778). For 97.7% of participants, less than 2.5% of reported foods went unmapped, with 75.7% of participants having complete mappings. Total polyphenol intake was 517 +/- 439 (mean +/- SD) mg/1000 kcal, largely from green tea, coffee, black tea, apples, wine, oranges, and blueberries. At the class level, polyphenols classified as organooxygen compounds, flavonoids, and cinnamic acids and derivatives were top intake contributors. At the compound level, cyptochlorogenic acid, neocholorogenic acid, and caffeic acid were top contributors. Lastly, the DII was 1.4 +/- 1.9, indicating the average diet had proinflammatory potential. Conclusions: Polyphenol Estimator offers an automated method to obtain total, class, and compound-level polyphenol estimates from dietary data to aid future efforts to understand polyphenol intake exposures and their biological impact on health.