Abstract: Accurate election outcome predictions are crucial for effective strategic planning and decision-making in political campaigns. By integrating historical election data, this study develops a robust predictive model for the Independent Electoral Commission (IEC) election results in South Africa. The model leverages advanced machine learning techniques and scenario analysis to forecast election results with improved accuracy. Despite the challenges posed by numerous small parties, data limitations, and the historical dominance of the African National Congress (ANC), the research highlights the importance of comprehensive data collection and real-time monitoring to enhance the predictive power of election models. This study contributes to the field of political analytics by providing a framework that can be adapted for other electoral contexts, supporting political parties, policymakers, and stakeholders in their strategic planning and decision-making processes.