Analyzing forest conversions and unraveling their drivers is a significant challenge for ecological research. The forests of northeastern China, including major temperate forest types in East Asia, constitute key ecological function zones. In this study, we investigated the changes in fractional forest cover (FFC) in Northeast China over the past 37 years using Landsat time series data and explored the underlying mechanism of FFC response to environmental changes with two methods: the partial correlation analysis between different time series and a SHAP-based explainable CatBoost algorithm at the point level. First, a probability-based random forest model was developed to classify forest and non-forest areas, achieving an average overall accuracy of 85% from 1987 to 2023. Pixel-by-pixel tracking of forest conversions over ten-year intervals revealed a significant net increase of more than 16×107 forest pixels. Notably, a declining trend in forest expansion (lost) was observed along altitude gradients above 200 m during four epochs. In the analysis of driving forces, our results indicated that FFC was positively correlated with temperature in 65% but negatively correlated with precipitation in 63% of the study region. Moreover, the impacts of temperature on increasing and decreasing FFC were contrasting: at altitudes above 200 m, increasing FFC exhibited a positive partial correlation with temperature, while decreasing FFC showed a nearly negative correlation with temperature. Furthermore, the predictive CatBoost model explained 58% of the increase in FFC, attributing it to variability in meteorology (mean annual temperature and precipitation), mean annual soil moisture, population density, and elevation. In comparison, these environmental factors accounted for 38% of the decrease in FFC. For total FFC changes (both increases and decreases), the optimized model achieved a precision of 40%. Among the driving factors, mean annual temperature played a predominant role in accounting for both total FFC changes and FFC increases. Meanwhile, mean annual precipitation was the most critical indicator triggering FFC decreases. Our findings provided valuable evidence and insights into the relationships between environmental factors and FFC dynamics in the context of sustainable development.