Our ultimate goal is to non-destructively evaluate mechanical properties of tissue-engineered (TE) cartilage using ultrasound (US). We used agarose gels as surrogates for TE cartilage. Previously, we showed that mechanical properties measured using conventional methods were related to those measured using US, which suggested a way to non-destructively predict mechanical properties of samples with known volume fractions. In this study, we sought to determine whether the mechanical properties of samples, with unknown volume fractions could be predicted by US. Aggregate moduli were calculated for hydrogels as a function of SOS, based on concentration and density using a poroelastic model. The data were used to train a statistical model, which we then used to predict volume fractions and mechanical properties of unknown samples. Young's and storage moduli were measured mechanically. The statistical model generally predicted the Young's moduli in compression to within <10% of their mechanically measured value. We defined positive linear correlations between the aggregate modulus predicted from US and both the storage and Young's moduli determined from mechanical tests. Mechanical properties of hydrogels with unknown volume fractions can be predicted successfully from US measurements. This method has the potential to predict mechanical properties of TE cartilage non-destructively in a bioreactor.