Biodiesel as a renewable alternative fuel for petroleum based diesel fuel produces lower emissions of all types (CO, HC ) except Nitrogen Oxides (NO x) when compared to the petroleum diesel fuel. Reducing Nitrogen Oxides produced from engines running on biodiesel is a challenging task to be able to meet the emission requirements. Knowledge of fuel blend could be very helpful for control and adaptation purposes to tune the engine control system parameters leading to lower NOx emission and improved engine performance. Biodiesel can be used in different blends with conventional diesel and estimating the percentage of the biodiesel fuel has become a new area of research in the past few years. Biomass content estimation based on fuel injection rate per engine cycle and the produced power from the engine is presented in this paper to fulfill this goal. The proposed method employs information about the produced power from a brake torque estimation algorithm and injected fuel from engine control unit (ECU). The designed estimator is tuned using the data collected from a developed engine model. Orthogonal Least Squares and Neural Network are the two system identification techniques used in this paper. The estimation results from the two identification methods are compared and illustrate that the designed estimator is accurate in both cases.