In this project, we analyze the Bank Marketing dataset using logistic regression to predict whether a customer will subscribe to a term deposit. We explore data preprocessing, feature selection, model evaluation using metrics like accuracy, sensitivity, specificity, ROC curve, and AUC. The model outperforms the baseline and reveals key factors influencing customer decisions, offering valuable insights for targeted marketing strategies.