Modelling the Potential Distribution of African Wormwood ( <i>Artemisia afra</i> ) Using a Machine Learning Algorithm‐Based Approach ( <scp>MaxEnt</scp> ) in Sekhukhune District, South Africa

<i>Artemisia afra</i> Jacq. ex Willd, commonly known as African wormwood, is a native medicinal plant that has been unsustainably harvested primarily for its leaves because of their medicinal properties. The unsustainable harvesting of this plant underscores the urgent need for conservation and management practices. This study, therefore, used the MaxEnt model of the potential distribution of <i>A. afra.</i> Sekhukhune District Municipality, South Africa. We used 105 sampled records and 27 environmental variables to model the potential spatial distribution of <i>A. afra</i> using the MaxEnt modeling approach. The predictions were performed using current climatic and topographic conditions. A significant portion of the area, 54.46%, is highly suitable for the distribution of <i>A. afra</i>, with various degrees. Precipitation contributed 33.6% to the suitability predictions, followed by NDVI, soil, and distance from rivers with 27.1%, 8.1%, and 5.7% respectively. <i>Artemisia afra</i> is predicted to be persistent in mountainous areas and along riverbanks. Higher elevated areas from 1000 to 1700 m are highly suitable for the persistence of <i>A. afra</i> species, as it remains cool and relatively moist under the changing climate. Conservation efforts should be focused on mountainous areas and along riverbanks. Rivers such as the Ngwaritsi, Motsephiri, and Steelpoort are in areas with highly suitable predictions. On the basis of the findings, we recommend conservation and management of highly suitable areas. A stakeholder-inclusive conservation framework is proposed to guide community-based protection of <i>A. afra</i> habitats.