Abstract: This study constructed a prognostic model for hepatocellular carcinoma（HCC） by screening genes related to ubiquitination and ferroptosis, and explored the impact of ubiquitination and ferroptosis-related genes on the prognosis of HCC. The DESeq2 package was used for differential analysis of the TCGA-LIHC dataset to obtain HCC differentially expressed genes（HCC＿DEGs）. The ubiquitination and ferroptosis differentially expressed genes（UBFE＿EDGs） obtained from the intersection of HCC＿DEGs, ubiquitination related genes（URGs）, and ferroptosis differentially expressed genes（FERR＿EDGs） were sequentially applied to LASSO regression analysis, univariate Cox regression analysis and multivariate Cox regression analysis to identify the optimal independent prognostic genes for constructing the ubiquitination and ferroptosis-related prognostic model（UBFE）. Survival curves, ROC curves, and calibration curves were used to evaluate the predictive accuracy of UBFE. Univariate Cox regression analysis and multivariate Cox regression analysis were performed to assess whether the UBFE risk score is an independent prognostic factor for HCC, and a nomogram was constructed. ssGSEA analysis and single-cell RNA sequencing data analysis were used to explore the correlations of UBFE with ubiquitination and ferroptosis. The results show that 45 UBFE＿EDGs were obtained from the intersection of HCC＿DEGs, URGs, and FERR＿EDGs. LASSO regression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis were performed sequentially, and two UBFE＿EDGs（DCAF13 and UBE2C） were identified for constructing the UBFE. Survival curves, ROC curves, and calibration curves analysis showed a significant correlation between the UBFE high-risk score group（HighUBFE） and poor prognosis in HCC patients, indicating good predictive accuracy of UBFE. The results of univariate Cox regression analysis and multivariate Cox regression analysis demonstrated that the UBFE risk score was an independent risk factor for HCC prognostic. The prediction accuracy of UBFE combined with TNM staging was higher, and the consistency between the predicted 1-year, 2-year, and 3-year survival rates of HCC patients and the actual survival rate was high in nomogram. Both ssGSEA analysis and single-cell RNA sequencing data analysis revealed a positive correlation between the UBFE risk score and ubiquitination, as well as a negative correlation with ferroptosis. The UBFE high-risk score group exhibited a stronger inhibitory effect on ferroptosis compared to the UBFE low-risk score group. The UBFE constructed in this study has shown good performance in predicting the prognosis of HCC patients. DCAF13 and UBE2C may affect the progression of hepatocellular carcinoma and patient prognosis through ubiquitination and ferroptosis pathways.