<p>The socioeconomic impacts of&#160;changes in climate-related&#160;and&#160;hydrology-related factors&#160;are increasingly&#160;acknowledged&#160;to affect&#160;the&#160;on-set&#160;of&#160;violent&#160;conflict.&#160;Full consensus&#160;upon&#160;the general&#160;mechanisms&#160;linking&#160;these&#160;factors&#160;with conflict&#160;is,&#160;however,&#160;still limited.&#160;The absence of full&#160;understanding&#160;of&#160;the non-linearities&#160;between all components and the lack of sufficient data make it&#160;therefore&#160;hard to address violent conflict risk on the long-term.&#160;</p><p>Although it is&#160;neither&#160;desirable nor feasible&#160;to make exact predictions,&#160;projections are a viable means&#160;to provide&#160;insights into potential&#160;future&#160;conflict risks&#160;and uncertainties thereof.&#160;Hence, making&#160;different&#160;projections is a&#8239;legitimate&#8239;way to deal with and understand these uncertainties, since the construction of diverse scenarios delivers insights into&#160;possible realizations of the future.&#160;&#160;</p><p>Through&#160;machine learning techniques, we&#8239;(re)assess the major drivers of conflict&#160;for the current situation&#160;in Africa, which are&#160;then&#160;applied to project the regions-at-risk following&#160;different&#160;scenarios.&#160;The model shows to accurately reproduce observed historic patterns leading to a&#160;high ROC score of&#160;0.91.&#160;We show that&#160;socio-economic factors&#160;are&#160;most dominant&#160;when&#160;projecting&#160;conflicts&#160;over&#160;the African continent.&#160;The projections show that there is an&#160;overall&#160;reduction in conflict risk&#160;as a result of&#160;increased&#160;economic welfare that&#160;offsets&#160;the&#160;adverse&#160;impacts&#160;of&#160;climate change and&#160;hydrologic variables.&#160;It must be noted, however, that these projections are based on current relations.&#160;In case the relations of drivers and conflict change in the future, the resulting&#160;regions-at-risk may change too.&#160;&#160; By identifying the most prominent drivers,&#160;conflict risk&#160;mitigation measures can be tuned more accurately to reduce the direct and indirect consequences of climate change&#160;on&#160;the population in Africa.&#160;As new and improved&#160;data becomes available, the model can be updated for more robust projections of conflict risk in Africa under climate change.</p>