Public building retrofit is an important pathway for reducing operational carbon emissions, but evidence-based technology prioritisation remains limited under real-world multi-technology retrofit conditions. This study develops an interpretable data-driven framework to identify priority technologies and technology co-adoption patterns for public buildings in China’s Hot Summer and Cold Winter (HSCW) region. Based on 218 completed retrofit projects, the carbon reduction rate (CRR) was used as the performance indicator, and 15 retrofit technologies were analysed using FDR-adjusted Mann–Whitney U tests, repeated-validation XGBoost–SHAP analysis, and Apriori association-rule mining. The projects showed substantial variation in CRR, with a mean of 24.98% and a median of 21.70%. Across five repeated 5-fold cross-validations, the predictive XGBoost model achieved a mean R² of 0.417 and a mean RMSE of 0.127. Roof insulation, external wall insulation, and ventilation system retrofit showed the strongest combined evidence and were classified as core technologies. Apriori analysis further revealed three empirical co-adoption patterns: integrated passive-envelope retrofit, solar-control and renewable-energy integration, and operational-management improvement. The findings suggest that retrofit planning in the HSCW region should prioritise envelope insulation and ventilation performance, while selecting shading, system, renewable-energy, and operational-control measures according to project-specific conditions.