Climate directly influences the epidemiology of vector-borne diseases at various spatial and temporal scales. Following the recent increased incidences of theileriosis in Zimbabwe, a disease mainly transmitted byRhipicephalus appendiculatus, we determined lethal temperatures for the species and current and possible future distribution using the machine learning algorithm ‘Maxent’.Rhipicephalus appendiculatuslarvae had an upper lethal temperature (ULT50) of about 44 ± 0.5 °C and this was marginally higher for nymphs and adults at 46 ± 0.5 °C. Environmental temperatures recorded in selected zonal tick microhabitats were below the determined lethal limits, indicating the ability of the tick to survive these regions. The resultant model under current climatic conditions showed areas with high suitability indices to the eastern, northeastern and southeastern parts of the country, mainly in Masvingo, Manicaland and Mashonaland Central provinces. Future predictions as determined by 2050 climatic conditions indicate a reduction in suitable habitats with the tick receding to presently cooler high elevation areas such as the eastern Highlands of Zimbabwe and a few isolated pockets in the interior of the country. Lowveld areas show low suitability under current climatic conditions and are expected to remain unsuitable in future. Overall, the study shows thatR. appendiculatusdistribution is constrained by climatic factors and helps identify areas of where occurrence of the species and the disease it transmits is highly likely. This will assist in optimizing disease surveillance and vector management strategies targeted at the species.