In order to address the issue of intelligent development in power tool design, this paper proposes an intelligent evaluation method for power tool design based on deep learning technology. The paper begins by summarizing the evaluation indicators for power tool design and constructing a hierarchical analysis model. It then utilizes FAHP to calculate the weight of each design indicator. Subsequently, pictures are collected and manually annotated to create a dataset for power tools. Finally, the dataset is refined and trained using the ResNet algorithm to develop an intelligent evaluation model for power tools, enabling the intelligent assessment of each evaluation indicator. By comparing the results of manual evaluation with those obtained through intelligent evaluation, it demonstrates the accuracy of the intelligent evaluation model based on ResNet algorithm and validates the effectiveness of this experimental approach.