Method for managing an internal combustion engine for a motor vehicle, the internal combustion engine comprising a plurality of elements, such as an intake manifold , at least one combustion chamber , an EGR valve and a turbocharger comprising a turbine , the control method comprising: - a step (E1) of receiving a plurality of first operating parameters (Rm, Car, α, β, δ, ε) of the internal combustion engine and a first reference parameter, which is referred to as the measured reference parameter (P Col mes ); - a step (E2) of estimating, by means of a neural network , at least one second operating parameter (F Col ) of the internal combustion engine and a second reference parameter, which is referred to as the estimated reference parameter (P Col est ), from all or some of the plurality of first operating parameters (Rm, Car, α, β, δ, ε); - a step (E3) of correcting, by means of an extended Kalman filter , the at least second operating parameter (F Col ) to obtain at least one corrected second operating parameter (F Col cor ), the correction step comprising a comparison between the measured reference parameter (P Col mes ) and the estimated reference parameter (P Col est ) to determine a correction gain (k), the correction of the at least second operating parameter (F Col ) being a function of the correction gain (k); - from the at least second corrected operating parameter (F Col cor ): - a step (E4) of controlling at least one element of the plurality of elements of the internal combustion engine, such as an intake valve at the inlet to the intake manifold and the EGR valve ; and - a step (E5) of estimating at least one third operating parameter, such as a temperature of the gases leaving the combustion chamber to prevent overheating at the turbine . - a step (E1) of receiving a plurality of first operating parameters (Rm, Car, α, β, δ, ε) of the internal combustion engine and a first reference parameter, which is referred to as the measured reference parameter (P Col mes ); - a step (E2) of estimating, by means of a neural network , at least one second operating parameter (F Col ) of the internal combustion engine and a second reference parameter, which is referred to as the estimated reference parameter (P Col est ), from all or some of the plurality of first operating parameters (Rm, Car, α, β, δ, ε); - a step (E3) of correcting, by means of an extended Kalman filter , the at least second operating parameter (F Col ) to obtain at least one corrected second operating parameter (F Col cor ), the correction step comprising a comparison between the measured reference parameter (P Col mes ) and the estimated reference parameter (P Col est ) to determine a correction gain (k), the correction of the at least second operating parameter (F Col ) being a function of the correction gain (k); - from the at least second corrected operating parameter (F Col cor ): - a step (E4) of controlling at least one element of the plurality of elements of the internal combustion engine, such as an intake valve at the inlet to the intake manifold and the EGR valve ; and - a step (E5) of estimating at least one third operating parameter, such as a temperature of the gases leaving the combustion chamber to prevent overheating at the turbine . <EOS>