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This dataset and trained artificial neural network (ANN) model support research on the seismic fragility assessment of corroded bridge structures. The uploaded files include: bridge_intensity_measures_input.txt: A tab-delimited text file containing parameters of corroded bridges and seismic intensity measures (e.g., PGA, PGV, Sa), used as input features for model training. bridge_damage_states_output.txt: A corresponding output file providing classified bridge damage states, derived from nonlinear time history analyses. The damage states are encoded as integer labels: 1: None 2: Slight 3: Moderate 4: Extensive 5: Complete trained_ann_fragility_model.mat: A MATLAB .mat file containing the trained ANN model designed to classify damage states based on corroded bridge parameters and seismic intensity measures. The model enables efficient prediction of seismic damage states for aging bridge structures without the need for computationally expensive simulations. These resources can be reused or extended for fragility curve generation, model benchmarking, or large-scale seismic risk assessments. Please cite this dataset as follows:xxxxx