Abstract: Improving agricultural carbon emission efficiency is of great significance for accelerating the green and low-carbon transformation of the agricultural sector, promoting high-quality agricultural development and fulfilling the dual-carbon strategic goals in Liaoning Province. Based on the accurate measurement of agricultural carbon emission efficiency in Liaoning Province by adopting the Super-Efficiency Slack-Based Measure (Super-SBM) model, this study systematically analyzes its dynamic spatiotemporal evolution characteristics from 2012 to 2022, and further explores the key driving factors and their internal action mechanisms by combining the Geodetector model and the Geographically and Temporally Weighted Regression (GTWR) model. The empirical results show that: 1) The total agricultural carbon emissions of Liaoning Province presented a distinct trend of first decreasing and then increasing during the period of 2012—2022, while the overall agricultural carbon emission efficiency maintained a steady upward trend with obvious stage characteristics; the agricultural carbon emission efficiency had significant spatial agglomeration features and prominent regional heterogeneity, among which Chaoyang, Dalian and Yingkou have long been in the high-efficiency leading areas with stable and excellent performance, Fuxin, Tieling, Huludao and other cities have long been trapped in the low-efficiency lagging areas with slow improvement speed, and Shenyang, Panjin, Benxi and other cities showed a fluctuating upward development state with great potential for efficiency improvement. 2) The dominant driving factors of agricultural carbon emission efficiency in Liaoning Province showed clear staged evolution characteristics, gradually transforming from the single dominance of resource utilization in the initial stage to the dual-core dominance of employment structure and industrial structure in the middle and late stages; meanwhile, the explanatory power of key influencing factors such as regional economic scale, technical application level, urbanization development rate and agricultural mechanization level continued to increase, fully reflecting the good development trend of multi-factor synergistic driving for agricultural carbon emission efficiency. 3) All the selected influencing factors presented significant spatial differentiation characteristics in the study area; the agricultural carbon emission efficiency in Liaoning Province is comprehensively restricted by multiple key factors including obvious differences in inter-regional economic development level, relative backwardness of advanced technical promotion level, insufficient investment in scientific and technological development, irrationality of production factor allocation structure and imperfectness of green development policy support system, thus it is urgent to realize the high-quality low-carbon transformation of agriculture through effective paths such as optimization of technical adaptability, coordinated allocation of key production factors, upgrading of agricultural industrial structure and improvement of green policy support system. In conclusion, this study not only systematically reveals the spatiotemporal evolution law and core driving mechanism of agricultural carbon emission efficiency in Liaoning Province, but also provides important scientific basis and practical path guidance for Liaoning Province to formulate differentiated and precise agricultural low-carbon transformation policies, and also offers useful reference for the green and low-carbon development of agriculture in other major grain-producing areas in Northeast China.