In this study, the differential pulse voltammetry (DPV) method was used to simultaneously determine bismuth and copper concentrations. A 25 bismuth and copper mixtures at the designed ratio were measured using the DPV technique. However, the overlapping differential pulse voltammograms obtained made it difficult to quantitatively analyze the concentrations based on adaptive peak current selection. To address this issue, the voltammograms were preprocessed using derivatization and peak subtraction. The second derivative voltammogram was found to be highly correlated with the copper-bismuth concentration ratio, resulting in improved fit and prediction accuracy. To further improve the accuracy and precision of the training and prediction results, XGBoost and Gradient Boosting regression models were applied. The XGBoost and Gradient Boosting regression models showed high accuracy and precision with r-squared values of 0.877 and 0.993 for copper, and 0.879 and 0.993 for bismuth, respectively. The mean recoveries of copper were 99.84% and 98.07%, while bismuth recoveries were 93.17% and 90.85% for XGBoost and Gradient Boosting, respectively. Additionally, cross-validation using 10 splits produced a mean score of 45.565 and a mean absolute error of 13.051 for copper, and a mean score of 13.600 and a mean absolute error of 10.920 for bismuth. Overall, the results indicate that the proposed method is an accurate and precise way to simultaneously determine bismuth and copper concentrations.