Abstract: Prostate cancer is a major cause of cancer-related deaths in men, with African populations often showing more aggressive disease and poorer outcomes. This study presents an interactive Streamlit-based clinical decision-support dashboard for analysing tumour heterogeneity in South African prostate cancer patients. The system integrates genomic and clinical features including tumour mutation burden, chromothripsis indicators, mutational entropy, lesion diversity, and subclonal burden. A composite tumour heterogeneity score was developed, and Non-negative Matrix Factorisation (NMF) was used for interpretable dimensionality reduction of mutational signatures. An XGBoost model was then applied to predict tumour heterogeneity scores. The dashboard enables exploration of cohort-level trends, patient-specific genomic profiles, mutational signature visualisation and new patient prediction of heterogeneity scores. Results show higher heterogeneity in advanced ISUP grade groups and a positive relationship between tumour mutation burden and heterogeneity.