This study addresses the challenge of linking European Union (EU) legislative definitions to the Sustainable Development Goals (SDGs) by developing a multilabel classification model. For this purpose, the AI-based multilabel classification model is designed to link EU legislative definitions with the SDGs. Different pre-processing techniques are applied to refine the dataset, including TF/IDF for feature extraction, PCA for dimensionality reduction, and Class Weights to handle imbalanced class problems that optimize the model’s performance (i.e., Weighted and Macro F-score). Support Vector Machine (SVM) outperforms with a 70.04% Weighted F-score by taking the text of the first four articles with preambles on the SDGs classification. The result underlines the proposed approach’s effectiveness in bridging EU legislative definitions with SDG frameworks. The developed model has been preserved for future policy analysis and sustainable development alignment applications. Finally, definitions of the EU legislation are successfully linked with the SDGs using SVM.