Aerobic granular sludge (AGS) is considered a promising technology for wastewater treatment. Furthermore, it is recognized that the stability of the process is related to the balanced growth of the suspended (floccular) and granular fractions. Therefore, the development of adequate techniques to monitor this balance is of interest. In this work the sludge volume index (SVI), volatile suspended solids (VSS) and total suspended solids (TSS) of mature AGS were successfully predicted with multilinear regression (MLR) models using data obtained from quantitative image analysis (QIA) of both fractions (suspended and granular). Relevant predictions were obtained for the SVI (R 2 of 0.975), granules TSS (R 2 of 0.985), flocs TSS (R 2 of 0.971), granules VSS (R 2 of 0.984) and flocs VSS (R 2 of 0.986). The estimation of the granular fraction ratio from the predicted TSS and VSS was also successful (R 2 of 0.985). The predictions help to avoid instability episodes of the AGS system, such as changes in biomass morphology, structure and settling properties.