Ticks are blood-feeding ectoparasites that transmit pathogens to animals and humans, ranking as the second most significant epidemiological agents next to mosquitoes. Ethiopia hosts seven genera and 60 species of ticks
however, our limited understanding of their spatial distribution and influencing factors hampers prevention and control efforts for ticks and tick-borne diseases. This study examined six predominant tick species in northwest Ethiopia: Amblyomma lepidum, A. variegatum, Hyalomma rufipes, Rhipicephalus decoloratus, R. evertsi, and R. praetextatus. Utilizing the MaxEnt model and QGIS, we identified key habitat factors influencing tick occurrence and mapped their potential distribution under current climate conditions. Our findings revealed that tick distribution and habitat suitability vary by species, all benefiting from precipitation during the coldest quarter, land cover, and densities of sheep and goats. The annual temperature range and mean diurnal range influenced the distribution of A. lepidum, A. variegatum, R. evertsi, and R. praetextatus, while cattle densities impacted A. variegatum, R. decoloratus, R. evertsi, and R. praetextatus. Habitat suitability for H. rufipes and R. decoloratus was influenced by the annual temperature range and mean diurnal range, respectively. Amblyomma lepidum and H. rufipes were primarily influenced by the mean temperature of the driest quarter, while A. variegatum, R. decoloratus, and R. evertsi were affected by the mean diurnal range and R. praetextatus by land cover. Amblyomma lepidum and H. rufipes preferred warmer lowland habitats, while A. variegatum, R. decoloratus, and R. evertsi thrived in the mid-highlands around Lake Tana, and R. praetextatus favored northeastern and northwestern lowlands. This study is the first to model tick distribution in Ethiopia, offering valuable insights into tick distribution and the risk of tick-borne diseases in northwest Ethiopia. We recommend further studies to incorporate additional environmental and human factors affecting tick populations, as well as diverse modeling and evaluation methods, while enhancing the quantity and quality of tick occurrence data.