Abstract: In order to solve the problem that the clothing compatibility method cannot fuse the complex relationship features among the items inside the suit well, resulting in low accuracy, this paper proposes a multi-layer mask Transformer model (MLMT) to solve the clothing compatibility problem. We proposed a Transformer-based encoder to fuse the style information of all items inside the suit, and we proposed a mask model to determine the compatibility of garments by comparing the correlation between items. It is validated on the polyvore-T public dataset, and the effectiveness of this method is demonstrated by comparing it with existing methods through experiments.