[Objective] This study aimed to analyze the spatiotemporal distribution of abandoned cropland in the core black soil protection zone of Jilin Province from 2000 to 2023, clarify the main driving factors behind abandoned cropland, and assess the soil and water conservation effects. The findings provide a theoretical basis for remote sensing monitoring of abandoned cropland and soil and water conservation research in similar regions.[Methods] Based on the Google Earth Engine (GEE) platform and Landsat imagery, the study integrates multidimensional characteristics and combines random forest and LandTrendr change detection methods to map the spatiotemporal distribution of abandoned cropland. Key driving factors were analyzed using geographic detectors. A comprehensive assessment of the soil and water conservation effects is performed using a combination weighting method based on AHP-EM-product normalization. [Results] ① The RF-LT model achieves an overall accuracy greater than 85%, and the Kappa coefficient of at least 0.8, indicating high classification accuracy and reliable results. ② The area of abandoned cropland initially increases, then experienced a fluctuating decline after peaking at 459 km2 in 2013. In terms of spatial distribution, it exhibits a trend of first increasing, then decreasing, and finally experiencing a local increase, with a relatively scattered distribution of abandoned cropland. ③ Night-time light intensity, average parcel area, and elevation are highly explanatory, with q-values all exceeding 0.4. Furthermore, the interaction between slope and average parcel area is the most significant, yielding a q-value of 0.997. ④ Soil and water conservation effect scores for abandonment of 5, 10, 15, 20, and over 20 years are 0.3886, 0.4773, 0.8014, 0.6044, and 0.4438, respectively, indicating an initial increase followed by a decrease. [Conclusions] The research results reveal the changing trends of abandoned cropland and its soil and water conservation effects in the core black soil region of Jilin Province, providing a theoretical basis for black soil protection and agricultural sustainable development.