This study monitored temperature using electronic sensors and developed a prediction model for compost maturity. The experiment used swine manure in a mechanical composting facility equipped with a screw-type agitator, and the composting process was conducted for 60 d during the summer season in South Korea. Four electronic temperature sensors were installed on the inner wall between the compost piles on Days 7, 14, 21, and 28 for daily temperature monitoring. Compost samples were collected daily for 60 d, and compost maturity was analyzed using the Solvita method. Multiple comparisons, correlations, and modeling were performed using the stat package in R software. The average compost pile temperatures was 39.1±3.9, 36.4±4.3, 31.3±4.5, and 35.4±8.1 on days 7, 14, 21, and 28, respectively, after composting. The average compost maturity according to the composting date was 3.61±0.60, 4.13±0.59, 4.26±0.47, and 4.32 ±0.56 on days 7, 14, 21, and 28, respectively. A significant negative correlation was observed between the compost composting periods (seven, 14, 21, and 28 d) and the temperature of all compost piles (p<0.05), where the correlation coefficients were -0.329, -0.382, -0.507, and -0.634, respectively. A significant positive correlation was observed between the compost composting periods (seven, 14, 21, and 28 d) and the maturity of the compost (p<0.05), where the correlation coefficients were 0.410, 0.550, 0.727, and 0.840, respectively. The model for predicting the maturation of the 14 d average compost pile according to the compost composting period and the average temperature for 14 d was y=0.026 x d – 0.021 x mt.x_14 d (mean temperature for 14 d) + 4.336 (R2=0.7612, p<0.001). This study can be considered a basic reference for predicting compost maturity by the proposed model using electronic temperature sensors.