Repetition suppression (RS), the diminished neural response to repeated stimuli, is a well-documented phenomenon potentially explained by predictive coding. This theory suggests that the brain anticipates incoming information, minimizing further processing for familiar stimuli. For example, fusiform face area (FFA) consistently shows decreased neural response to repeated presentation of the same faces. According to the traditional model of visual processing, information progresses from the lower brain regions' superficial cortical layers to the higher areas' middle layers. Within this framework, the FFA, as a higher processing region, is thought to show reduced prediction error in its middle layers with face repetition, leading to RS. To investigate this, we leveraged high-resolution laminar BOLD-fMRI. Overcoming the technical challenges of laminar BOLD-fMRI, we measured RS to faces across the FFA's cortical layers. Our preliminary findings show a pronounced RS effect predominantly in the middle cortical layers of the FFA, supporting predictive coding's role in efficient visual processing through top-down feedback. Further, we propose exploring RS effects in lower visual areas expecting greater RS effects in superficial and deep layers than in middle layers. Moreover, we hypothesise enhanced connectivity from FFA's superficial and deep layers to the early visual cortex's superficial layers, indicative of refined top-down predictions. Our preliminary results support the hypothesis that during the repetition of faces, there is a reduction in prediction error signals received by the middle layers of the FFA. We also showcase the potential of laminar BOLD-fMRI to elucidate the complexities of cortical processing.