The wildfires have a significant detrimental impact on the forest ecosystem. Extreme weather events such as high temperatures, wind speed and drought triggered by climate change increase the frequency and severity of wildfires. The rising incidence of extreme weather conditions demonstrates the necessity for the development of new approaches for the assessment of fire risk, which is the primary objective of this study. In this study, the determination of wildfire risk areas for all months of the year was carried out in geographic information systems (GIS) by using the Analytical Hierarchy Process (AHP) model, a well-known Multi-Criteria Decision-Making Method (MCDM). The study area was selected as the Çanakkale province of western Türkiye, situated within the Mediterranean Climate Zone and experiencing an increased frequency of large fires. 12 criteria have been designated in the AHP model, including one vegetation (forest areas), three topographic (slope, aspect, elevation), three anthropogenic (distance from settlements, agricultural areas and roads), five climates (air temperature, relative humidity, precipitation, wind speed, and land surface temperature generated using Landsat thermal bands). For the climate factors, unlike the general approach adopted regarding climate data in previous studies, this study analyzed the fire risk according to the extreme meteorological conditions (EMC) in addition to normal climate conditions (NCC). Thus, this study conducted risk analysis with two different data sets: NCC and EMC, where vegetation, topographic, and anthropogenic factors are common, but climate data are different. According to NCC and EMC risk analysis, where the risk was evaluated in 5 degrees between no risk (1) and very high risk (5), July is the riskiest NCC, and EMC period, and medium (3) and mostly high (4) risk groups dominate the study area. To analyse and compare the risk maps obtained from NCC and EMC, the areas burned in previous forest fires in the study area were determined using the Normalized Burn Ratio (NBR) index produced from Landsat satellite images. In the comparisons considering the burned areas for previous forest fires, the risk analysis, which is fed by EMC, was found to give better results in determining wildfire risk areas. Another notable finding of the study is that the increase in EMC frequency and severity leads to an extension of the fire season towards both autumn and spring.