A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Master’s in Life Sciences of the Nelson Mandela African Institution of Science and TechnologyKi-67, p53, and BCL-2 are now emerging as markers for classifying breast cancer, guiding therapy and predicting treatment responses and prognosis. Restricted data currently exist on these molecular markers in Tanzania; hence, we assessed the expressions of Ki-67, p53, and BCL-2 and associated them with clinical histopathological features in breast cancer patients attending Muhimbili referral hospital in Tanzania. This retrospective cross-sectional hospitalbased study was carried out between 2016 and 2017. For this research, only women were chosen with proven breast cancer, complete clinical history and accessible paraffin block samples. Tissue samples were immunohistochemically stained for Ki-67, p53, and BCL-2, with respect to their specific Monoclonal Mouse Anti-Human. The relationship between Ki67, p53 and BCL-2 expressions and clinical histopathological features was determined using a multinomial linear regression model. Only 76 cases met the inclusion criteria for this study, with a mean age of 51.32 ±14.28 years. Of these, 86.4% were stage III and IV, whereas 83.5% cases had grade 2 and grade 3. Upon immunostaining, 85.5% and 57.9% were Ki-67 and BCL-2 positive, respectively. Log-linear analysis showed no statistically significant association among biomarkers expression and CH features. However, multinomial linear regression showed higher possibility for association between Ki-67+, p53- and BCL-2+ with age, grade, stage and tumor (T) stage. BCL-2 was positively correlated with Ki-67 expression contrary to p53, which was negatively correlated with BCL-2. Conclusively, there is evidence of correlation between the studied markers with CH features making these markers potential tools for evaluating treatment response in individualized therapeutic schemes.