When used for the comprehensive evaluation of shale oil sweet spots in the Yingxiongling area, the traditional lithology-electric crossplots face many challenges, including low accuracy and difficulties in selecting optimal sensitive parameters and establishing adaptive evaluation criteria. To address these limitations, we propose a comprehensive evaluation approach that integrates principal component analysis (PCA)-based multi-parameter weighting with the analytic hierarchy process (AHP). This approach facilitates the scientific selection of sensitive parameters and the comprehensive quantitative evaluation of shale oil sweet spots in the Yingxiongling area. Six core parameters are identified through Pearson correlation analysis: porosity, oil saturation, total organic carbon (TOC) content, rock pyrolysis-derived free hydrocarbons content (S₁), brittle mineral content, and carbonate content. The weights of these parameters are determined based on the loadings and variance contribution rates of the principal components. Accordingly, a linearly weighted comprehensive evaluation model for sweet spots, along with criteria for classification and comprehensive evaluation, is established. Under the guidance of this novel model, daily oil flow rates of 17.61 m³ and 13.7 m³ were tested from sweet spot intervals in wells C12 and C20, respectively, while a post-fracturing daily oil flow rate of 20.5 m³ was tested in well CP13. For the horizontal section of well CP13, the comprehensive index showed a significant positive correlation with the liquid production contribution rate detected using an oil-phase tracer. These results demonstrate that the proposed model is suitable and can be widely applied in shale oil sweet spot evaluation.