Breast cancer is one of the most prevalent malignancies among women, accounting for about a quarter of all new diagnoses worldwide. Treatment and prognosis vary according to histological subtype and stage at diagnosis. Because of heterogeneity in treatment responses, biomarkers that predict clinical outcomes are crucial. Recently, the neutrophil-to-lymphocyte ratio (NLR) has emerged as a promising prognostic biomarker. This study analyzed retrospective data from patients diagnosed with breast cancer between 2008 and 2022, focusing on complete blood count (CBC) findings and their prognostic impact. Absolute values and ratios (neutrophils, monocytes, basophils, platelets, and lymphocytes) were derived from CBCs performed before and throughout treatment. The results showed that NLR, monocyte/lymphocyte ratio (MLR), and platelet/lymphocyte ratio (PLR) serve as independent prognostic factors, while the basophil-to-lymphocyte ratio did not reach significance. These hematologic features, along with clinical data, were used to train supervised machine learning models classifying poor prognosis as recurrence or death within 10 years, and good prognosis otherwise.