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Dirofilariasis is helminthiasis caused by a nematode of the genus Dirofilaria. This disease mainly affects mammals, and humans are a random host and biological dead end for the parasite, and therefore the disease often has a severe course. The principal warm-blooded host of dirofilariae is the canine family species, mainly dogs. Dirofilariasis is transmitted through Culex, Aedes, and Anopheles mosquitoes. Since the spread of dirofilariasis depends on the presence of vectors, the climate has a great influence on it. Climate warming contributes to the expansion of the range of mosquitoes to the north. European Russia is a zone of stable risk of transmission of dirofilariasis due to global climate change, favorable natural and climatic conditions, as well as the presence of a high infection with dirofilariasis canines. This work aims to analyze the influence of the climatic factor on the spread of dirofilariasis. To do this, we simulated the spatial distribution of the incidence of dirofilariasis using geospatial analysis tools. The method of modeling ecological niches with optimization according to the method of maximum entropy (Maxent) was chosen. This method is used when modeling ranges of species based on the known locations where the species was found (presence data) and geospatial variables that characterize the landscape and climatic conditions. The method allows modeling the potential range of the studied species, as well as the potential nosoareal of the disease, which is determined by the range of its pathogen. For modeling, the most general climatic parameters that can affect the transmission of dirofilariasis were used: mean annual air temperature, mean annual precipitation, the maximum temperature of the warmest month, and minimum temperature of the coldest month. As the main parameter is air temperature, the most important climatic factor is thermal conditions. The average annual precipitation does not have a significant effect, since the greater part of the nosoareal lies in areas with normal and insufficient precipitation (southern forest, forest-steppe, and steppe zones) and with significant interannual fluctuations. The most favorable territories of European Russia include the Black Earth Region, the Rostov Oblast, the Krasnodar Kray and the Crimea. The resulting model generally corresponds to the models published in the scientific literature, based on different principles, which suggests that the method used is suitable for further study of the risk of dirofilariasis spread.