Hepatocellular carcinoma (HCC) is the sixth most common malignancy and the fourth leading cause of cancer related death worldwide. China covers over half of cases, leading HCC to be a vital threaten to public health. Despite advances in diagnosis and treatments, high recurrence rate remains a major obstacle in HCC management. Multi-omics currently facilitates surveillance, precise diagnosis, and personalized treatment decision making in clinical setting. Non-invasive radiomics utilizes preoperative radiological imaging to reflect subtle pixel-level pattern changes that correlate to specific clinical outcomes. Radiomics has been widely used in histopathological diagnosis prediction, treatment response evaluation, and prognosis prediction. High-throughput sequencing and gene expression profiling enabled genomics and proteomics to identify distinct transcriptomic subclasses and recurrent genetic alterations in HCC, which would reveal the complex multistep process of the pathophysiology. The accumulation of big medical data and the development of artificial intelligence techniques are providing new insights for our better understanding of the mechanism of HCC via multi-omics, and show potential to convert surgical/intervention treatment into an antitumorigenic one, which would greatly advance precision medicine in HCC management.