Breast cancer, the most prevalent malignancy among women worldwide, exhibits significant heterogeneity, particularly in the tumor microenvironment (TME), which poses challenges for treatment. Spatial transcriptomics (ST) has emerged as a transformative technology, enabling gene expression analysis while preserving tissue spatial architecture. This provides unprecedented insights into tumor heterogeneity, cellular interactions, and disease mechanisms, offering a powerful tool for advancing breast cancer research and therapy. This review aims to synthesize the applications of ST in breast cancer research, focusing on its role in decoding tumor heterogeneity, characterizing the TME, elucidating progression and metastasis dynamics, and predicting therapeutic responses. We also explore how ST can bridge molecular profiling with clinical translation to enhance precision therapy. The key scientific concepts of review included the following: We summarize the technological advancements in ST, including imaging-based and sequencing-based methods, and their applications in breast cancer. Key findings highlight how ST resolves spatial heterogeneity across molecular subtypes and histological variants. ST reveals the dynamic interplay between tumor cells, immune cells, and stromal components, uncovering mechanisms of immune evasion, metabolic reprogramming, and therapeutic resistance. Additionally, ST identifies spatial prognostic markers and predicts responses to chemotherapy, targeted therapy, and immunotherapy. We propose that ST serves as a hub for integrating multi-omics data, offering a roadmap for precision oncology and personalized treatment strategies in breast cancer.