An electronic noses system including six metal oxide sensors was used to predict the characteristics of shelf-life of soybean curd. Soybean curd was stored at two different temperatures defined as low temperature(5$^{C}$) and high temperature(25$^{C}$). Resistance changes of the sensors were measured 13 times for 19 days at low temperature and 19 times for 120 hours at high temperature. Three different analytical methods such as graphical analysis(GA), principal component analysis(PCA), and cluster analysis(CA) were used to analyze sensors outputs. The ratio of resistance was decreased according to increasement of shelf-life. Using PCA it was possible to predict freshness and shelf-life time of soybean curds. Also, using CA it was possible to simplify an electronic nose system. Electronic nose system could be an efficient method to predict shelf-life and to evaluate quality in foods.