A fault in the primary mass flow sensor of an aircraft engine bleed air system can cause significant deterioration of overall system performance. This project uses an analytical model of the bleed air system to create a fault detection and accommodation scheme for the mass flow sensor. The analytical model uses information from the upstream and downstream pressure sensors to predict the output of the mass flow sensor. Faults are detected by comparing the output from the sensor with the predicted output from the analytical model. A fuzzy logic rule base is used to determine the degree of the flow sensor fault. The degree of the sensor fault is used to determine the inaccuracy of the faulty sensor output. A corrected estimation of the flow rate is then created using a weighted algorithm consisting of the predicted flow rate from the analytical model and the flow rate from the faulty sensor. The analytical model is also used to detect and accommodate transient responses from the flow sensor including signal overshoot, oscillations and time constant errors. A MATLAB computer simulation is conducted to evaluate the performance of the bleed air system degrades slightly in the event of a fault of the flow sensor. While the sensor fault will degrade the performance of the bleed air system, the degradation is not significant, and the bleed air system is able to maintain acceptable performance in the presence of faults.