The Caatinga Biogeographic Dominion comprises the most biodiverse and densely populated Seasonally Dry Tropical Forests and Woodlands in the world, with a variety of endemic fauna and flora species that have developed strategies to establish in an environment with water deficit. Its biodiversity is threatened by anthropic pressure, such as deforestation and fires, which can intensify the effects of climate change, such as rising temperatures and long periods of drought. Thus, our aim was to estimate the climate change impacts on the woody flora of the Caatinga. We selected about 10% of native Caatinga woody flora (131 species) from a random sample of a list of native species of the Caatinga. We then used the WorldClim bioclimatic variables to model ecological niche for all species for present conditions (1970-2000) and two future scenarios (2061 to 2080) under climate change: one intermediate (SSP2-4.5) and one pessimistic (SSP5-8.5). We evaluated trends in temperature and precipitation in Caatinga between current and future climate change scenarios and used species distribution models to project the potential distribution of species for present conditions and future scenarios. We then created maps for potential species richness under each scenario. Our results show risks of generalized biodiversity loss with the increased temperature and decreased precipitation in Caatinga under global warming projections. Our models revelled that for present conditions, high-altitude regions have the greatest suitability for concentration of higher species richness, mainly in the Chapada Diamantina. In climate change scenarios, our results show a generalized reduction in projected species richness, with higher decrease in modelled species richness under the pessimistic scenario. Our results underscore the need for conservation actions to mitigate the impacts of climate change that has affected the world's most populous semi-arid region.Graphical AbstractGraphical Abstract Description : The graphical summary synthesizes our analysis of the impacts of climate change on the woody flora of the Caatinga, located in the semiarid region of Brazil and considered the largest seasonally dry tropical forest in the Americas. The first panel displays the location of Caatinga in South America and highlights that 131 woody plant species were selected from a random sample of the Caatinga woody flora for species distribution modelling. The central section illustrates the use of 19 bioclimatic variables from the WorldClim database for both present conditions (1971-2000) and two future climate scenarios SSP-2.45 (intermediate) and SSP-5.85 (pessimistic) for the period 2061-2080. To assess climatic trends, we generated 1,000 random points across the Caatinga, extracting values of Bioclim precipitation and temperature variables (BIO1, BIO12, BIO16, and BIO17) for each scenario to evaluate predicted changes in climate in future scenarios. Species distribution models were developed using eight different algorithms and multiple data strategies (presence-only, presence-pseudoabsence, and background points) to estimate present and future climatic suitability. The right panel illustrates key results: violin plots show projected increases in temperature and decreases in precipitation, while maps depict reductions in modelled species richness under both climate scenarios. High-altitude areas, which currently support greater richness, are especially vulnerable. Together, the visual elements present a clear narrative of biodiversity loss under climate change. The figure underscores the urgent need to integrate climate projections into conservation planning to mitigate species loss and preserve ecosystem services in Brazil's semiarid landscapes.