<p>Triple-negative breast cancer (TNBC), being one of the most aggressive subtypes of breast malignancies, is characterized by poor prognosis and limited treatment options. As a leading cause of cancer-related mortality among women, TNBC poses unique clinical challenges due to the absence of effective targeted therapies. Conventional treatment strategies, including chemotherapy, often suffer from significant drawbacks such as drug resistance and intolerable side effects, underscoring an urgent need for innovative approaches to improve therapeutic outcomes. A defining hallmark of TNBC is its markedly altered cellular metabolism, which not only supports tumor growth and survival but also contributes to therapy resistance. Elucidating these metabolic alterations could provide critical insights into potential vulnerabilities that may be exploited for therapeutic intervention. This review provides a comprehensive overview of the major metabolic pathways that are dysregulated in TNBC and their relevance to disease progression and therapeutic intervention. Finally, we explore recent advances in metabolomics-driven precision medicine, highlighting the integration of artificial intelligence and machine learning approaches, covering aspects such as data processing, feature selection, and model construction that can accelerate the advancement of personalized treatment strategies for TNBC.</p>