Device for deriving the operating state of an agricultural working machine on the basis of signals from sensors , comprising: one or more sensors for providing in each case an output value for a current parameter of a component of the working machine , and a processing unit which is connected to the sensors and is programmed to derive the operating state of the working machine on the basis of the measured values from the sensor(s) and/or values derived therefrom using a hidden Markov model , wherein a state transition matrix (A), elements of an emission probability matrix (B) for the probability of an observation being caused by a particular state and a vector (Π) for describing an input state can be applied to the processing unit in order to derive the operating state (S) of the working machine therefrom, and the derived operating state can be displayed to an operator on a display panel of an operator input device and/or is used to control components of the working machine , characterized in that the processing unit is programmed to derive elements of the emission probability matrix (B) from the measured values from the sensor(s) , and in that the processing unit is programmed to select a model for the respective operating mode of the working machine , on the basis of measured values from sensors and a position determination system , from models for field work, road travel, maintenance and approach to a headland and to select the state transition matrix (A) and/or the vector (Π), on the basis of the selected model for the operating mode, from a database which stores different state transition matrices (A) and/or vectors (Π) for different operating modes of the working machine . one or more sensors for providing in each case an output value for a current parameter of a component of the working machine , and a processing unit which is connected to the sensors and is programmed to derive the operating state of the working machine on the basis of the measured values from the sensor(s) and/or values derived therefrom using a hidden Markov model , wherein a state transition matrix (A), elements of an emission probability matrix (B) for the probability of an observation being caused by a particular state and a vector (Π) for describing an input state can be applied to the processing unit in order to derive the operating state (S) of the working machine therefrom, and the derived operating state can be displayed to an operator on a display panel of an operator input device and/or is used to control components of the working machine , characterized in that the processing unit is programmed to derive elements of the emission probability matrix (B) from the measured values from the sensor(s) , and in that the processing unit is programmed to select a model for the respective operating mode of the working machine , on the basis of measured values from sensors and a position determination system , from models for field work, road travel, maintenance and approach to a headland and to select the state transition matrix (A) and/or the vector (Π), on the basis of the selected model for the operating mode, from a database which stores different state transition matrices (A) and/or vectors (Π) for different operating modes of the working machine . <EOS>