As human activities increasingly disrupt the environment, significant changes have occurred in the human-environment relationship in China's mountainous regions. Assessing and predicting the dynamics of social-ecological system vulnerability (SESV) in the Qinling-Daba Mountains is crucial for ecological conservation and sustainable development in China's mountainous regions, offering valuable insights from a social-ecological perspective. This study employs the Spatially Explicit Resilience-Vulnerability (SERV) model to decompose SESV into three dimensions: exposure risk, sensitivity, and adaptive capacity, using a total of 48 indicators. Quantitative assessments from 2000 to 2020 reveal the spatial distribution patterns of SESV and its dimensions within the Qinling-Daba Mountains of southern Shaanxi. Subsequently, a support vector machine model was constructed, and by comparing the accuracy of models optimized by three different algorithms, the optimal model was selected to predict the spatiotemporal distribution and evolutionary characteristics of SESV and its dimensions in the Qinling-Daba Mountains from 2020 to 2050. The results indicate that: (1) The overall SESV in the Qinling-Daba Mountains generally falls within a medium to low vulnerability range, exhibiting a spatial distribution that is higher in the central areas and lower in the northern and southern regions. (2) The accuracy of the support vector machine model optimized by the particle swarm algorithm is the best, and selecting an appropriate number of training samples can further improve prediction performance. (3) The predictions show a significant reduction in SESV in the Qinling-Daba Mountains, with the social-ecological systems developing in a positive direction. The exposure risk shows a convergence with SESV, and regional differences have decreased. However, the sensitivity and adaptive capacity continue to display a "higher in the west, lower in the east" pattern, with no alleviation in regional differences. Based on the evaluation and forecasting results, targeted and systematic management strategies are proposed. On one hand, under the socio-ecological system framework, mountainous region development needs to balance socio-economic growth with environmental and ecological needs. The research focus should emphasize the trade-offs between the economy and the environment in mountainous areas. On the other hand, policymakers should be aware that ecological improvements driven by administrative constraints and financial incentives may lead to rebound effects. Therefore, it is crucial to promote eco-industries aligned with local resource endowments and ecological characteristics while moderately developing industry. This study aims to provide a reference for SESV assessment and prediction through an analysis of a typical mountainous region in China.