Background:　Recurrence　is　a　major　factor　leading　to　treatment　failure　and　death　in　gastric　cancer　(GC)　patients　following　surgical　resection.　Importantly,　the　prediction　of　recurrence　is　critical　in　improving　clinical　outcomes.　We　isolated　a　group　of　microRNAs　(miRNAs)　and　evaluated　their　usefulness　as　prognostic　markers　for　the　recurrence　of　GC.　Patients　and　methods:　A　total　of　65　GC　patients　were　selected　for　systematic　analysis,　29　patients　with　recurrence　and　36　patients　without　recurrence.　Firstly,　miRNAs　microarray　and　bioinformatics　methods　were　used　to　characterize　classifiers　from　primary　tumor　samples　(n　=　8).　Following,　we　validated　these　predictors　both　in　frozen　fresh　and　paraffin-embedded　tissue　samples　(n　=　57)　using　quantitative　PCR.　Results:　We　have　identified　17　differential　miRNAs　including　10　up-regulated　and　7　down-regulated　miRNAs　in　recurrence　group.　Using　k-top　scoring　pairs　(k-TSP)　method,　we　further　ascertained　hsa-miR-375　and　hsa-miR-142-5p　as　a　classifier　to　recognize　recurrence　and　nonrecurrence　cases　both　in　the　training　and　test　samples.　Moreover,　we　validated　this　classifier　in　34　frozen　fresh　tissues　and　38　paraffin-embedded　tissues　with　consistent　sensitivity　and　specificity　with　training　set;　among　them,　15　cases　were　matched.　A　high　frequency　recurrence　and　poor　survival　were　observed　in　GC　cases　with　high　level　of　hsa-miR-375　and　low　level　of　hsa-miR-142-5p　(P　＜　0.001).　In　addition,　we　evaluated　that　hsa-miR-375　and　hsa-miR-142-5p　were　involved　in　regulating　target　genes　in　several　oncogenic　signal　pathways,　such　as　TP53,　MAPK,　Wnt　and　vascular　endothelial　growth　factor.　Conclusion:　Our　results　indicate　that　the　combination　of　hsa-miR-375　and　hsa-miR-142-5p　as　a　predictor　of　disease　progression　has　the　potential　to　predict　recurrence　risk　for　GC　patients.