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Populations of  Anogeissus leïocarpa  (DC.) Guill. &amp; Perr. in Niger have come under increasing demographic as well as climatic pressures, which are threatening indigenous tree species that contribute substantially to income generation in rural households. Understanding how climate makes the species particularly vulnerable to extinction and how range shifts may be driven by climatic change is more urgent than ever. One powerful approach for the assessment of the species distribution is habitat modelling, which is a promising tool for priority setting, conservation decision-making and overall support for species conservation. This study combined environmental variables found at sites where species occurrence has been confirmed and analyzed the results to predict future spreading patterns. High variation inflation factor (VIF) values were found for the series of interpolated climate. The study results demonstrate that soil type, elevation, bio 2 (mean diurnal range (Mean of monthly (max temp − min temp))) and 18 (precipitation of warmest quarter) contribute greatly to the models. The study shows that the species is predicted to have some suitable current suitable area (100,926.1 km 2 ); the South West Niger is the most important region for the protection of the habitat in Niger. The habitat area of  Anogeissus leïocarpa  (DC.) Guill. &amp; Perr. is projected to increase drastically suitability areas in future climate up to 2.73% (RCP 4.5) and decrease up to 5.99% (RCP 8.5) according to CCSM4 and MIROC 5. Based on the outcome of the models, the climatic conditions could boost and prevent the development of  Anogeissus leïocarpa  (DC.) Guill. &amp; Perr. and their existence. The models and habitat suitability maps derived here with the approach of ecological niche factor analysis can facilitate the prediction of habitat quality under different conservation and management regimes of  Anogeissus leïocarpa  (DC.) Guill. &amp; Perr. The findings are invaluable for the implementation of conservation strategies and domestication programmes based on  Anogeissus leïocarpa  (DC.) Guill. &amp; Perr.

Forecasting the distribution of Anogeissus leïocarpa (DC.) Guill. & Perr. by using an ensemble modelling in Niger, West Africa