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Abstract When extreme hydrometeorological events threaten the United States, quantitative precipitation forecasts (QPFs) from the National Centers for Environmental Prediction’s Weather Prediction Center (WPC) provide critical decision support to help mitigate risks to life and property. This study builds on previous work by providing an updated benchmark of WPC QPF skill for extreme precipitation events from 2012 to 2024, through evaluating the 6- and 24-h accumulations for the day 1–3 lead times. Extreme precipitation is defined using three thresholds: the 99th and 99.9th percentile precipitation values of all wet-site days from 2012 to 2024 for each National Oceanic and Atmospheric Administration (NOAA) River Forecast Center (RFC) region and the 2-yr average recurrence interval from the NOAA Atlas 14. WPC forecasts are verified against Stage IV quantitative precipitation estimates. Forecast skill is assessed seasonally, regionally, and temporally for the 1200 UTC forecast cycle. Results show that WPC forecasts of extreme precipitation have improved over time. The highest skill is observed along the West Coast, where events are dominated by atmospheric rivers from late fall through early spring. Forecasts in these regions often retain skill through day 3. The East Coast shows the second-highest skill, particularly in fall and winter, when extreme precipitation occurs from tropical and synoptic systems. Skill is lowest in inland areas, especially in the summer months when precipitation systems are weakly forced, smaller in scale, and often underforecasted by WPC. These events rarely show skill after a day 1 lead time. Significance Statement Extreme precipitation remains a primary driver of billion-dollar disasters in the United States, underscoring the growing need for accurate quantitative precipitation forecasts. By benchmarking the skill of National Oceanic and Atmospheric Administration’s (NOAA) Weather Prediction Center forecasts of extreme precipitation, we can understand where regional and seasonal weaknesses exist and evaluate the current boundaries of precipitation predictability. These insights are essential for guiding future advancements in operational forecasting and model development.