B3 breast lesions, classified as lesions of uncertain malignant potential, present a significant di-agnostic and therapeutic challenge due to their heterogeneous nature and variable risk of pro-gression to malignancy. These lesions, which include atypical ductal hyperplasia (ADH), papil-lary lesions (PL), flat epithelial atypia (FEA), radial scar (RS), lobular neoplasia (LN), and phyl-lodes tumors (PT), occupy a "grey zone" between benign and malignant pathologies, making their management complex and often controversial. This article explores the diagnostic difficul-ties associated with B3 lesions, focusing on the limitations of current imaging techniques, in-cluding mammography, ultrasound, and magnetic resonance imaging (MRI), as well as the chal-lenges in histopathological interpretation. Core needle biopsy (CNB) and vacuum-assisted bi-opsy (VAB) are widely used for diagnosis, but both methods have inherent limitations, includ-ing sampling errors and the inability to determine malignancy in some cases definitively. The therapeutic approach to B3 lesions is nuanced, with treatment decisions strongly influenced by factors such as lesion size, radiological findings, histopathological characteristics, and patient factors. While some lesions can be safely monitored with watchful waiting, others may require vacuum-assisted excision (VAE) or surgical excision to rule out malignancy. The deci-sion-making process is further complicated by the discordance between the BIRADS score and biopsy results, as well as the presence of additional risk factors, such as microcalcifications. This review provides an in-depth analysis of the current diagnostic challenges and treatment strate-gies for B3 lesions, emphasizing the importance of a multidisciplinary approach to management. By synthesizing the most recent research, the article aims to provide clinicians with a clearer understanding of the complexities involved in diagnosing and treating B3 breast lesions while highlighting areas for future research, such as Artificial Intelligence and Genomics, to improve diagnostic accuracy and patient outcomes.