Unlike many other countries, tropical regions such as Indonesia still lack publications on pedotransfer functions (PTFs), particularly ones dedicated to the predicting of soil bulk density. Soil bulk density affects soil density, porosity, water holding capacity, drainage, and the stock and flux of nutrients in the soil. However, obtaining access to a laboratory is difficult, time-consuming, and costly. Therefore, it is necessary to utilise PTFs to estimate soil bulk density. This study aims to define soil properties related to soil bulk density, develop new PTFs using multiple linear regression (MLR), and evaluate the performance and accuracy of PTFs (new and existing). Seven existing PTFs were applied in this study. For the purposes of evaluation, Pearson’s correlation (r), mean error (ME), root mean square error (RMSE), and modelling efficiency (EF) were used. The study was conducted in five soil types on Bintan Island, Indonesia. Soil depth and organic carbon (SOC) are soil properties potentially relevant for soil bulk density prediction. The ME, RMSE, and EF values were lower for the newly developed PTFs than for existing PTFs. In summary, we concluded that the newly developed PTFs have higher accuracy than existing PTFs derived from literature. The prediction of soil bulk density will be more accurate if PTFs are applied directly in the area that is to be studied.