To generate an ROC curve, you must first have a set of predictions from your classification model and the actual outcomes. The curve is then plotted with the True Positive Rate (TPR) on the y-axis and the False Positive Rate (FPR) on the x-axis. Tools like Python libraries (e.g., scikit-learn) can be used to generate these curves easily.