The main goal of the study is to solve the problem of losing customers or clients in various financial organizations, especially in the banking sector. It investigates the use of Random Forest algorithm and the Power BI dashboard which helps to forecast churn and improve retention strategies. Historical data—transactions, demographics, and usage patterns—is collected and a thorough analyzation is done with the help of Power BI to provide a dynamic dashboard that provides insights in real-time. Combining data analytics technologies and predictive skills with their retention initiatives can help banks increase their efficacy and efficiency. Economic loss and operational difficulties are brought on by customer attrition. The outcome of this study suggests a method for forecasting customer attrition in banks that combines Power BI’s amazing data visualization techniques with Random Forest’s highly accurate predictive skills. The Random Forest algorithm integrates multiple decision trees to make predictions in a precise and expandable way. Moreover, it has the capability of handling large data sets.