Drilling of oil and gas wells utilize drilling mechanical energy to crush formation rocks through drill bits. Due to the friction with the formation rocks, the bit cutters suffer a continuous wear with the progress of the drilling causing reduction in rate of penetration. Real-time bit wear is a challenge in drilling as there is no absolute physical model. This paper presents new philosophy based on control engineering systems to simulate bit behavior and estimate the transferred and wasted mechanical energy to predict drilling performance efficiency. Analytical model has been developed to predict drilling performance by analyzing the real-time transferred drilling mechanical energy consumed by the drill bits, the model will assist in optimizing the hydraulic energy and take the proper time decision to pull the dulled bits. The model consists of a first order differential equation solved to predict the effect of drilling parameters on drill bit wear; while, the bit wear equation enters in a second order differential equation solved by Laplace transformation, and expressed as a transfer function representation which allows in analyzing the drilling performance, and also expressed as real-time of bit displacement achieved by the input drilling energy. The poles of denominator of the transfer function have been analyzed as a complex conjugate pairs; the location of the real part of the complex roots indicates the amount of real-time consumed mechanical energy by the drilling bits to destroy formation rocks. While, the location of imaginary roots indicates the amount of wasted mechanical energy due to bit wear. The effect of hydraulic energy on drilling performance has been simulated using closed loop transfer function, which allows for monitoring the wasted mechanical energy, and the wasted hours of bit life consumed in extra cutting due to insufficient hydraulic energy. The results show that the visual representation for poles location allows real-time monitoring for the performance of the transferred mechanical energy due to both bit dullness and to insufficient hydraulic energy explicitly. The results also show high decline rate in transferred mechanical energy always occurs within small values of bit dullness compared with that occurred in large values of bit dullness, which confirm the real field observations. The comparison with field examples proves the model reliability in predicting the drilling performance.