Abstract: Based on daily temperature data of 86 weather stations during winter producing season from 1961 to 2017 in Guangdong Province, the temporal and spatial distribution of extreme chilling was analyzed. The return periods of extreme chilling at county level were calculated with the theory of generalized extreme value distribution to provide technical support for extreme chilling risk assessment and early warning together with real-time meteorological disaster prevention and mitigation in winter planting areas. Results showed that there was a general downward trend of the extreme values of chilling accumulation in main winter planting zones. Zhanjiang and Meizhou had declined significantly since the mid-1980s, while Maoming, Shaoguan and Guangzhou had declined significantly since the 21st century. The extreme minimum temperature followed a curve trending generally downward first and upward later on, with a significant rising in Shaoguan from later 1980s while a descending in Guangzhou in the last five years. The order of the number of extreme value stations of chilling accumulation was 1970s > the 21st century > 1990s > 1960s > 1980s. The order of the number of stations of extreme minimum temperature was 1960s > 1990s > the 21st century > 1970s > 1980s. The theoretical forecast values of cold disaster of 2, 5, 10, 20, 50, and 100 year return period showed obvious zonal distribution characteristics. The chilling accumulation diminished from the north to the south and the extreme minimum temperature was higher in the south and lower in the north, which was consistent with the distribution trend in the actual occurrence of cold damage. Typical cases showed more extended chilling return periods in the south than in the north. In Zhanjiang and Maoming, the main producing areas of winter crops in Guangdong Province, the return period of cold damage was long, the probability of extreme cold damage was small but the damage was heavy, and the area of winter crops was in the front rank, which should be paid attention. Our results could provide scientific reference for local government and relevant departments in Guangdong Province to guide winter planting and develop countermeasures against climate change.