Dating population divergence within species from molecular data and relating such dating to climatic and biogeographic changes is not trivial. Yet it can help formulating evolutionary hypotheses regarding local adaptation and future responses to changing environments. Key issues include statistical selection of a demographic and historical scenario among a set of possible scenarios, and estimation of the parameter(s) of interest under the chosen scenario. Such inferences greatly benefit from new statistical approaches including approximate Bayesian computation - Random Forest (ABC-RF), the latter providing reliable inference at a low computational cost, with the possibility to take into account prior knowledge on both biogeographical history and genetic markers. Here, we used ABC-RF, including independent information on evolutionary rate and pattern at microsatellite markers, to decipher the evolutionary history of the African arid-adapted pest locust, Schistocerca gregaria . We found that the evolutionary processes that have shaped the present geographical distribution of the species in two disjoint northern and southern regions of Africa were recent, dating back 2.6 Ky (90% CI: 0.9 – 6.6 Ky). ABC-RF inferences also supported a southern colonization of Africa from a low number of founders of northern origin. The inferred divergence history is better explained by the peculiar biology of S. gregaria , which involves a density-dependent swarming phase with some exceptional spectacular migrations, rather than a continuous colonization resulting from the continental expansion of open vegetation habitats during more ancient Quaternary glacial climatic episodes.