Abstract: The stability of open-pit mine slopes plays a critical role in ensuring the safety and economic efficiency of large-scale mining operations. However, this stability is governed by a complex interplay of multiple factors, including inherent rock mass properties, slope height, and slope gradient. These factors introduce significant levels of uncertainty and nonlinearity into the mechanical response of the slope. Traditional evaluation methods, such as the limit equilibrium method (LEM) and singular numerical simulation (NS) approaches, are often ineffective in providing a comprehensive perspective. LEM focuses on the safety factor based on a predefined slip surface, and NS provides detailed stress–strain fields. However, neither approach can easily synthesize diverse mechanical indicators into a unified decision-making framework. To address this limitation, in this paper proposes a novel integrated evaluation system that fuses multi-source numerical simulation data with multi-criteria decision-making (MCDM) theories. Specifically, the system employs set pair analysis (SPA), entropy weighting, and the technique for order of preference by similarity to ideal solution (TOPSIS). A systematic numerical modeling is utilized to generate a comprehensive dataset, which is then processed using the proposed SPA–Entropy–TOPSIS framework. The findings are summarized as follows: (1) Sensitivity analysis of influencing factors reveals that within the SPA–Entropy–TOPSIS comprehensive evaluation hierarchy, the geological strength index (GSI) exerts the most significant impact on the relative closeness (stability degree) of the slope. This is followed by slope height, while the bench slope angle has a relatively minor but measurable influence. This ranking emphasizes that the intrinsic quality of the rock mass is the primary determinant of stability in the investigated geological environment. (2) Among the various mechanical responses monitored, the maximum horizontal stress, maximum displacement magnitude, and volume ratio of the plastic zone are identified as the core indicators. These three parameters capture the essential characteristics of slope deformation, stress redistribution, and failure evolution, providing a robust physical basis for the mathematical model. (3) A critical challenge in traditional analysis is the inconsistency of single mechanical indicators during stability judgment. For instance, a slope may exhibit acceptable displacement levels while showing an alarmingly large plastic zone. This study underscores the need for a multidimensional collaborative evaluation approach, which can reconcile conflicting indicators to provide a more reliable safety assessment. (4) The proposed SPA–Entropy–TOPSIS evaluation system effectively integrates multi-source numerical simulation data. By utilizing the entropy weighting method, the framework assigns objective weights to each indicator based on their information entropy, successfully correcting the subjective biases inherent in traditional expert-based weighting methods. Furthermore, SPA enhances the model by addressing the "certainty–uncertainty" relationship between the slope’s current state and its threshold limits. Overall, the proposed system demonstrates high applicability and precision in the stability assessment of open-pit mine slopes. It transforms fragmented numerical data into a prioritized ranking of stability states, providing mine engineers and decision-makers with a quantitative, scientifically rigorous tool for safety grading, risk management, and design optimization. This methodology offers a new paradigm for transitioning from empirical safety factor judgments to multi-index integrated intelligent decision-making in geotechnical engineering.