Three models were examined to predict C aromaticity (f(a)) of biochars based on either their elemental composition (C, H, N and O) or fixed C (FC) content. Values of f(a) from solid state C-13 nuclear magnetic resonance (NMR) analysis with Bloch-decay (BD) or direct polarisation (DP) techniques, concentrations of total C, H, N, and organic O, and contents of FC of 60 biochars were either compiled from the literature (dataset 1, n = 52) or generated in this study (dataset 2, n = 8). Models were first calibrated with dataset 1 and then validated with dataset 2. All models were able to fit dataset 1 when atomic H to C ratio (H/C) < 1 (except two ash rich biochars) and to estimate f(a) of HF treated biochars (H/C < 1). Model 1, which was based on values of H/C only and calibrated with a root mean square of error (RMSE) of 0.04 f(a)-unit (n = 41), could predict the experimental data with a RMSE = 0.02 f(a)-unit (n = 6). Model 2, which was based on biochar elemental composition data, showed the most accurate prediction, with a RMSE of 0.03 f(a)-unit (n = 41) for the calibration data, and of 0.02 f(a)-unit (n = 6, H/C < 1) for the validation data. Model 3, which was based on contents of FC and C, and modified with a correction factor of 0.96, displayed the highest RMSE (0.06 f(a)-unit, n = 19) among the three models. Models 1 and 2 did not work properly for samples having either an H/C ratio > 1, high concentrations of carbonate or high inorganic H. These models need to be further tested with a wider range of biochars before they can be recommended for classification of biochar stability.