<p>Rockbursts often cause severe damage to excavation working faces, equipment failure, and personnel casualties. To rationally process fuzzy and uncertain information in rockburst prediction, a rockburst intensity evaluation model integrating unascertained measure and evidence theory was developed. First, based on rockburst intensity classification criteria, single-index measurement functions for rockburst intensity evaluation were established using unascertained measure theory. Addressing the uncertainty in indicator weighting, evidence theory was employed to fuse multiple subjective and objective weights obtained through analytic hierarchy process, Delphi method, CRITIC, entropy weight, and anti-entropy weight methods. Subsequently, 16 sets of underground engineering rockburst data were selected as samples for intensity evaluation, with comparative analysis conducted against multi-dimensional cloud model, entropy-normal cloud model, RS-TOPSIS methods, and actual field observations. Finally, the proposed model was applied to assess rockburst intensity in the SPD9 cavern of Shuangjiangkou Hydropower Station. The results demonstrate that the proposed unascertained measure-evidence theory model achieves higher accuracy compared with other methods, with evaluation outcomes aligning well with actual observations. This model provides theoretical guidance for practical rockburst intensity assessment in engineering projects.</p>