The Mars Science Laboratory spacecraft landed an approximately 900 kg rover on Mars on 5 August 2012. Similar to past Mars missions, the spacecraft recorded inertial measurement unit data and radar altimeter measurements, but its aeroshell was also instrumented with flush atmospheric data system sensors that captured the pressure distribution on the vehicle during hypersonic and supersonic flight regimes. The rich data set enables a comprehensive postflight analysis of the vehicle's trajectory, atmosphere, and aerodynamics. This paper demonstrates a comprehensive statistical estimation methodology and applies it to the large but disparate data set to reconstruct the vehicle's entry performance, while using several statistical estimation methods, specifically the extended Kalman filter, unscented Kalman filter, and adaptive filter, which concurrently estimate both the state and the uncertainties. The results of the analysis shows good agreement between the estimated states, preflight predictions, and independent reconstructions, while also demonstrating the efficacy of the comprehensive statistical estimation method for Mars entry, descent, and landing reconstruction.