Background. Transcriptional dysregulation plays a critical role in the onset and development of malignant tumors. Employing gene dysregulation to forecast the change of tumors is valuable for cancer diagnosis. However, the prognostic prediction for HCC using combined gene models remains insufficient. Methods. The expression profiles of GSE103512 and TCGA-LIHC were downloaded. Gene Ontology (Go) was used to evaluate the overlapping differential genes (DEG) in TCGA and GSE103512. The core genes in the critical module most significantly related to HCC were obtained by WGCNA. Eight genes most significantly related to HCC and OS were identified by reweighted coexpression network analysis and Cox regression. Results. We selected eight genes, FZEB1, CDK1, RAD54L, COL1A2, ATP1B3, CASP8, USP39, and HOXB7. Moreover, we constructed an eight-gene model and forecasted the prognosis of HCC. ROC curve of the eight-mRNA prognostic model was screened out ( AUC = 0.635 ), suggesting that this model exhibited a good prediction performance. Survival analysis showed that the survival rate of patients in the high-risk group was significantly lower than that in the low-risk group. Conclusion. The eight-mRNAs model might forecast the OS of HCC patients and advance remedial decision-making.