Yes, regularization plays a crucial role in predictive modeling for cancer. By preventing overfitting, regularization ensures that the models developed are robust and can accurately predict outcomes such as patient survival rates, response to treatment, and recurrence of cancer. This is particularly important in developing prognostic models that can guide clinical decision-making.