With the continuous expansion of transportation infrastructure construction, traditional highway maintenance decision making models face challenges such as data silos, decision-making lag, and uneven resource allocation. This paper deeply analyzes the value connotation of big data technology in highway maintenance decision-making, and examines key issues in current integration applications, including uneven data quality, lack of technical standards, insufficient talent teams, and difficulties in input output evaluation. On this basis, the paper constructs a precision decision-making implementation path based on optimization of data collection at the perception layer, enhancement of intelligent analysis at the platform layer, improvement of decision support at the application layer, and establishment of sound institutional mechanisms at the guarantee layer. This research provides theoretical guidance and practical references for enhancing the scientific nature and effectiveness of highway maintenance decision-making.