Background: The application of robotic-assisted liver resection (RALR) in hepatocellular carcinoma (HCC) has been steadily increasing, but comprehensive comparative data with laparoscopic liver resection (LLR) remain limited. This study aims to systematically evaluate the short-and long-term outcomes, recurrence patterns, quality of life (QoL), and cost-effectiveness of RALR versus LLR for Barcelona Clinic Liver Cancer (BCLC) stage 0/A HCC. Methods: A multicenter propensity score-matched analysis was conducted using long-term follow-up data from 24 national centers, including 1,761 patients with BCLC stage 0/A HCC who underwent RALR or LLR. Prognostic indicators such as overall survival (OS) and recurrence-free survival (RFS) were analyzed, along with cost-effectiveness measures, including quality-adjusted life years (QALYs) and incremental cost effectiveness ratios (ICERs). Variables such as surgical costs, recurrence treatment costs, and QoL were meticulously recorded at different time intervals. Cox proportional hazards regression was used to assess factors influencing prognosis. Results: RALR demonstrated comparable OS and RFS rates to LLR but exhibited differences in complication profiles and recurrence patterns. Although RALR had higher initial surgical costs, it showed significant long-term economic advantages due to reduced recurrence-related and complication-related expenses, as well as improved QALY. At lower willingness-to-pay (WTP) thresholds, LLR demonstrated better cost-effectiveness. However, RALR displayed greater advantages at higher thresholds. Conclusions: This study provides robust evidence supporting the use of both RALR and LLR for patients with BCLC stage 0/A HCC, highlighting their clinical and economic benefits. While RALR may involve higher initial costs, it remains a highly cost-effective option and has the potential for broader adoption as initial costs decrease. These findings emphasize the value of minimally invasive approaches in improving long-term outcomes and optimizing healthcare resource utilization, particularly in resource-limited settings.