Aim: This study aimed to predict progression-free survival (PFS) in patients with early glottic cancer using radiomic features on dual-energy computed tomography iodine maps. Methods: Radiomic features were extracted from arterial and venous phase iodine maps, and radiomic risk scores were determined by univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator regression with tenfold cross-validation. The Kaplan-Meier method was used to evaluate the association between radiomic risk scores and PFS. Results: Patients were stratified into low-risk and high-risk groups using radiomics, the PFS corresponding rates with statistical significance between the two groups. The high-risk group showed better survival, benefiting from laryngectomy. Conclusion: Radiomics could provide a promising biomarker for predicting the PFS of early glottic cancer patients.