Hepatocellular carcinoma (HCC) has a poor prognosis even after curative surgery, due to the high frequency of early intrahepatic recurrence (IHR). Conventional staging systems are almost completely inadequate, and need to be complemented by novel tools. To this end, many investigators have performed DNA microarray analysis on the basis of genome-wide information. However, so far, few studies have been able to truly account for the clinical efficacy of DNA microarray analysis in HCC. To address this dilemma, we used a supervised learning method with information of 7070 genes from 33 HCC samples, to construct a 12-gene predictor for early IHR, and then evaluated its predictive performance in 27 independent HCC samples. Our 12-gene predictor correctly predicted early IHR or non-recurrence in 25 (93%) of the 27 independent samples. This predictive value is higher than that of any other system currently available, suggesting that our system can serve as a robust tool for accurate prediction of early IHR of HCC. I emphasize in this mini-review that, although there are some technical issues to resolve prior to clinical use, DNA microarray technology can provide molecular basis to initiate “bench to bedside” translation, which cannot be easily reached with other methods.