This study develops a multilayer neural network model (hereinafter referred to as an "AI model") to predict the deterioration of light fixtures installed in highway tunnels. The AI model is based on the results of an inspection of light fixture installations classified in the "C" category, and uses 15 environmental factors that are considered to affect the degradation rate of light fixtures as inputs, and outputs the progress of degradation at the time of the next inspection. A logistic regression model was also developed. Then, test data that had not been used for training were input to the constructed model to make predictions, and the prediction reproducibility was evaluated. The results showed that the AI model was able to predict lamp deterioration more accurately than the logistic regression model. Furthermore, a sensitivity analysis of the input data was conducted to identify the variables that are important for improving the accuracy of the model.