In the competitive construction market, accurately predicting project completion time is crucial for contractors to make informed bids and ensure profitability. Traditional methods for predicting completion times are becoming obsolete in the face of advancing technology. This study introduces a novel approach by integrating Building Information Modeling (BIM) and Back Propagation (BP) neural network to forecast project completion times. We employed the BIM technology for detailed project analysis and the BP neural network for making predictions. This methodology was applied to a specific engineering project, where pre-completion predictions were made and then compared to actual outcomes to assess deviations and validate the approach. The results demonstrate that combining BIM with a BP neural network significantly enhances the accuracy of completion time predictions. This research confirms the effectiveness of this integrated method, offering a more reliable and scientific tool for project time management in the construction industry.