The article explores how the mirror neuron system (MNS) enables understanding of others' intentions through action observation. It proposes that the MNS functions within a predictive coding framework, which involves minimizing prediction error across cortical levels to infer the most likely cause of an observed action. This approach aligns with empirical Bayesian inference, where prior expectations guide the interpretation of sensory inputs. The MNS is considered to consist of three key areas: the superior temporal sulcus (STS), the inferior parietal lobule (area PF), and the premotor area F5. These areas are reciprocally connected, forming a hierarchical structure that supports the inference of intentions from actions. The article discusses the role of predictive coding in action perception, where the brain uses a hierarchical model to infer the causes of observed actions. This involves comparing predicted kinematics with observed kinematics to generate prediction errors, which are then used to update the representation of motor commands. The predictive coding framework allows the MNS to infer intentions even when observed actions are identical, by incorporating contextual information that provides empirical priors. The study also highlights the importance of generative models in motor control and perception. These models help predict the sensory consequences of motor actions, which are then used to refine motor control. In the context of action observation, the same generative models can be inverted to infer the intentions of others. This process is supported by the hierarchical organization of the MNS, where higher-level areas provide context and prior information that guide lower-level processing. The article concludes that the MNS can be understood within a predictive coding framework, which provides a mechanistic account of how the brain infers intentions from actions. This framework not only explains the functional organization of the MNS but also connects it to broader principles of perception and action. The predictive coding account of the MNS is supported by empirical evidence and offers a coherent explanation of how the brain infers the intentions of others through action observation.The article explores how the mirror neuron system (MNS) enables understanding of others' intentions through action observation. It proposes that the MNS functions within a predictive coding framework, which involves minimizing prediction error across cortical levels to infer the most likely cause of an observed action. This approach aligns with empirical Bayesian inference, where prior expectations guide the interpretation of sensory inputs. The MNS is considered to consist of three key areas: the superior temporal sulcus (STS), the inferior parietal lobule (area PF), and the premotor area F5. These areas are reciprocally connected, forming a hierarchical structure that supports the inference of intentions from actions. The article discusses the role of predictive coding in action perception, where the brain uses a hierarchical model to infer the causes of observed actions. This involves comparing predicted kinematics with observed kinematics to generate prediction errors, which are then used to update the representation of motor commands. The predictive coding framework allows the MNS to infer intentions even when observed actions are identical, by incorporating contextual information that provides empirical priors. The study also highlights the importance of generative models in motor control and perception. These models help predict the sensory consequences of motor actions, which are then used to refine motor control. In the context of action observation, the same generative models can be inverted to infer the intentions of others. This process is supported by the hierarchical organization of the MNS, where higher-level areas provide context and prior information that guide lower-level processing. The article concludes that the MNS can be understood within a predictive coding framework, which provides a mechanistic account of how the brain infers intentions from actions. This framework not only explains the functional organization of the MNS but also connects it to broader principles of perception and action. The predictive coding account of the MNS is supported by empirical evidence and offers a coherent explanation of how the brain infers the intentions of others through action observation.