Peripheral vision plays a critical role during scene categorization. The rapid extraction of global features in peripheral vision would allow a rudimentary representation of the scene, known as the gist, associated with prior knowledge about regularities in the visual environment. This knowledge could then be used to rapidly categorize the scene, but also to generate predictions about objects it contains. Previous studies suggest that predictions generated from peripheral vision improve the categorization of objects in central vision. However, visual perception is a dynamic phenomenon which alternates between ocular fixations on an object of interest and saccades towards the periphery to fixate new objects. The present study aims to investigate how predictions based on the scene context in peripheral vision influence gaze orientation on objects in peripheral vision. Twenty-five participants performed a go/no-go saccadic task on an object (either animal or furniture) displayed in peripheral vision (7° of eccentricity), either on the left or the right side of a central fixation. A scene background was simultaneously displayed in peripheral vision, either semantically congruent with the object (outdoor scene/animal and indoor scene/furniture) or incongruent (indoor scene/animal and outdoor scene/furniture). Participants were instructed to make a saccade towards the object belonging to a target category or maintain fixation at the centre when it belonged to the distractor category. When the target object was absent (and thus, the distractor object was present), participants made more false alarms towards the distractor in an incongruent scene (but congruent to the target object) than in a congruent one. This suggests that scene context influences gaze orientation on objects in peripheral vision. We are currently conducting a new study in which we manipulate the onset asynchrony (SOA) between scene and object to further investigate the influence of predictions based on scene-context on gaze orientation in peripheral vision.