This study aimed to predict radiotherapy outcome for breast cancer patients using clinical and dosimetric parameters through logistic regression analysis. The study made use of One Thousand, Four Hundred and Twenty-Two (1422) patients treated for breast cancer at the NSIA Cancer Centre, Lagos University Teaching Hospital (LUTH), Lagos State. Multivariate logistic regression analysis is performed in R Studio, with the level of significance set at p<0.05. The results show that among the dosimetric parameters, only V95 (volume receiving 95% of the prescribed dose) was a significant predictor (p=0.026) of radiotherapy outcome. Higher V95 values are associated with better outcomes. Regarding clinical parameters, cancer staging emerged as a significant predictor, with stage 3 (odds ratio=4.76, p=0.001) and stage 4 (odds ratio=16.17, p<0.001) being associated with poorer outcomes compared to stage 0. Other parameters entered into the model did not significantly predict radiotherapy outcome in this cohort of breast cancer patients. The study highlights the importance of V95 and cancer staging in predicting radiotherapy outcomes and can inform future treatment planning and patient management strategies; which vis-à-vis assist in achieving the goal three of the United Nations Sustainable Development Goals (SDG).