Discovery, identification, and informatics of low molecular weight peptide are extensively rising in the field of proteomics research. In this study, we analyzed protein profiles to discover peptide based biomarker for twelve different soybean seeds with three different agronomic types using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). For optimization of SELDI-TOF MS in soybean seed proteome analysis, four different extraction buffers were tested with urea solubilization buffer, thiourea/urea solubilization buffer, phenol extraction buffer, and modified trichloroacetic acid (TCA)/acetone precipitation/urea solubilization extraction buffer. Two different type of ProteinChip arrays, cation exchange (CM10) and anion exchange (Q10), applied to profile peptides. Among the four different extraction buffers, phenol extraction was selected to protein extraction methodology. Numbers of detected peak cluster in twelve soybean seeds were 125 at CM10 and 90 at Q10 array in the mass range from 2 to 40 kDa. Among them, 82 peak clusters at CM10 and 33 peak clusters at Q10 array showed significantly different peak clusters at p<0.00004 (CM10) and p<0.00005 (Q10) among twelve different soybean cultivars. Moreover, 29 peak clusters at CM10 and 17 peak clusters at Q10 array were detected in all cultivars as an ‘universally existed peptide’. In comparison with three different agronomic types, total of 55 peak clusters (CM10) and 23 peak clusters (Q10) were significantly different peak clusters at p<0.00004 and p<0.0001, respectively. In these probability levels, soybean seeds were well discriminated into different cultivar and different type with each other. Also we could find several specific peptide biomarkers for agronomic type.