The results showed that these prediction models could effectively distinguish glioblastoma patients in the MGMT promoter methylated group from the unmethylated group, with AUCs of 0.861, 0.850, 0.867, 0.852, 0.874, 0.889 in the T1WIintra model, T1WIprei model, CE-T1WIintra model, CE-T1WIprei model, T1WIintra+prei model, CE-T1WIintra+prei model respectively, indicating that MRI deep learning could be used for the assessment of MGMT promoter methylation status in glioblastoma patients. Here, MGMT is linked to glioblastoma.