The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 NOAA Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the period 2020-59 (centered in the year 2040) as compared to the 1966-2005 historical period. A Microsoft Excel workbook is provided which tabulates quantiles of change factors derived from downscaled climate datasets at grid cells closest to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida considering only the best models, and the SSP3-7.0 future emissions scenario. The change factors were computed as the ratio of projected future to historical precipitation depths fitted to extreme-precipitation data using a constrained maximum likelihood approach (CML) for NASA Earth Exchange Global Daily Downscaled Projections (NASA) and Localized Constructed Analogs version 2 (LOCA2) datasets. The quantiles of change factors are tabulated by duration (1, 3, and 7 days) and return period (5, 10, 25, 50, 100, 200, and 500 years) for percentiles (non-exceedance probabilities) of 5, 16, 50, 84, and 95 percent considering all available models within each dataset and the SSP3-7.0 future emissions scenario. Best models are listed in Best_models_lists_CMIP6.xlsx and were identified based on how well the models capture the climatology and interannual variability of four climate extreme indices using the Model Climatology Index (MCI) and the Model Variability Index (MVI) of Srivastava and others (2020). The four indices consist of annual maxima consecutive precipitation for durations of 1, 3, 5, and 7 days compared against the same indices computed based on the PRISM and SFWMD gridded precipitation datasets for five climate regions: climate region 1 in Northwest Florida, climate region 2 in North Florida, climate region 3 in North-Central Florida, climate region 4 in South-Central Florida, and climate region 5 in South Florida. The PRISM dataset is based on the Parameter-elevation Relationships on Independent Slopes Model interpolation method of Daly and others (2008). The South Florida Water Management District’s (SFWMD) precipitation super-grid is a gridded precipitation dataset developed by modelers at the agency for use in hydrologic modeling (SFWMD, 2005). This dataset is considered by the SFWMD as the best available gridded rainfall dataset for south Florida. Best models were selected based on MCI and MVI evaluated within each individual downscaled dataset.