Background: Ageing-related genes (ARGs) have been implicated in liver hepatocellular carcinoma (LIHC) progression, but their prognostic mechanisms remain poorly understood. This study systematically investigated the role of ARGs in LIHC through comprehensive bioinformatics analysis. Methods: I identified differentially expressed ARGs (|logFC| >1, false discovery rate (FDR) < 0.05) by using The Cancer Genome Atlas (TCGA) data (374 LIHC vs. 50 normal tissues) and constructed a 10-gene prognostic model by performing LASSO-Cox regression analysis. Functional enrichment, protein–protein interaction (PPI) networks, and immune infiltration analyses were performed to uncover key regulators among ARGs. Results: The ARG-based risk model (including PRKCD, E2F1, and HDAC1) effectively stratified patients into high/low-risk groups with distinct survival outcomes (p < 0.001, AUC = 0.871 at 5 years). Subsequent network analysis unexpectedly identified CDC20 as the central hub gene of the ARG interactome. CDC20 showed significant overexpression in LIHC tissues (p < 0.05, GEPIA) and strong correlation with poor prognosis. Functional studies revealed its association with mitotic nuclear division pathways and immune cell infiltration by using TIMER dataset. Conclusion: Our unbiased analysis revealed CDC20 as a critical node in the ARG-associated network of LIHC. These findings suggest CDC20 may mediate the prognostic effects of ARGs through cell cycle regulation and immune modulation, suggesting its potential as a therapeutic target for LIHC.