###### Abstract
Furthermore, some essential bridges, such as those within critical highway networks, may undergo regular maintenance regardless of their deterioration levels. Both deterioration and maintenance drive the overall performance of a bridge deck, yet high-performing bridges may not require extensive maintenance and may not be deteriorating rapidly. Understanding the precise dynamics and considering other influential factors can provide further insights into the behavior of different types of bridge decks with wearing surfaces throughout their service life. The selection and design of a wearing surface consider factors such as traffic weight, volume, speed, construction requirements, and maintenance costs [8]. Understanding the correlation, interaction, and other relationships between these metrics and other factors could assist in guiding decision-making processes and minimizing accumulated costs and disruptions caused by significant repairs and replacements. Although some studies have examined the impact of wearing surfaces on bridge deck deterioration, a comprehensive understanding of the relationship between bridge performance, deterioration, maintenance, and wearing surfaces is still needed [9, 10]. In this work, we address this research gap by formulating our analysis for all types of wearing surface areas with respect to maintenance, deterioration, and performance. This study introduces several novel aspects in the analysis of deck wearing surfaces:  
* Our research focuses on assessing bridge deck-wearing surfaces within the state of Nebraska, which was previously an unexplored area in the existing literature. * In addition to understanding the deterioration of bridge deck wearing surface, a bridge health metric examined extensively in the literature, we broaden our focus to encompass other dimensions, including performance and bridge maintenance. * While prior studies have examined the influence of wearing surfaces on bridge deck deterioration, there remains a need for a comprehensive understanding of the intricate interaction between variables such as bridge performance, deterioration, maintenance, and other variables in understanding bridge wearing surfaces. * We explore the relationship between influential variables in predicting bridge deck maintenance to discern whether they exhibit linear or non-linear associations. Moreover, we employ state-of-the-art explainable techniques like partial dependency plots (PDP) and Shapley additive explanation (SHAP) alongside performance metrics to gain further insights into the results of the maintenance of bridge deck-wearing surfaces. The remainder of this paper is structured as follows: Section 2 reviews prior literature, motivating our research. Section 3 offers an in-depth exploration of the methodology, including data collection and processing, the formulation of bridge health metrics, statistical tests, and machine learning modeling techniques, all aimed at understanding the critical aspects of bridge deck performance, deterioration, and maintenance. Section 4 presents the results of our statistical analysis and machine learning modeling. Section 5 is focused on a comprehensive discussion of our findings and their implications, leveraging state-of-the-art explainable methods. Finally, in Section 6, we conclude the paper by summarizing our findings and outlining potential avenues for future research.