Abstract: Qinling-Daba Mountains, located in China's north-south climatic transitional zone in China, have been sensitive to climate change with a vulnerable environment. This region is also a hot area for studying the vegetation responses to climate under global warming. Based on the observation data of 89 meteorological stations and remote sensing vegetation data, we explored the spatio-temporal patterns of ten bioclimatic indicators, including annual average temperature, annual precipitation, and accumulated temperature in the Qinling-Daba Mountains from 1982 to 2015. The sensitivity of vegetation to bioclimatic indicators was discussed according to the geographical detector and correlation analysis. The spatio-temporal distributions of bioclimatic indicators in the Qinling-Daba Mountains were summarized as follows, (1) The annual average temperature decreased from southeast to northwest in Qinling-Daba Mountains, while the annual precipitation decreased from south to north. In addition, both of them decreased from low to high altitude. (2) The distribution of accumulated temperature, accumulated temperature days, and warm index showed that the overall heat condition in the eastern Qinling-Daba Mountains was optimal, while the western part was relatively poor. The warmest month's average temperature distribution was highly consistent with the warm index. (3) The dryness increased from south to north, with the drought frequency increasing from west to east. (4) Meanwhile, the temporal variations of bioclimatic indicators were characterized by significantly improved heat conditions, insignificantly improved water conditions, drying hydrothermal conditions, and increasing regional drought. The bioclimatic indicator changes affected the vegetation coverage of the Qinling-Daba Mountains. On the one hand, bioclimatic indicators reflecting high temperature or accumulated heat and drought frequency had a higher explaining capacity for vegetation distribution. On the other hand, vegetation was significantly correlated to accumulated temperature in most stations. The vegetation change in most areas was affected by the heat indicators, while the moisture and hydrothermal indicators dominated the vegetation change in low-latitude areas. Our study will provide theoretical support for vegetation change prediction and ecological sustainability protection in China's north-south climatic transitional zone.