MALDI MS images were normalised against the total ion current (TIC) during the initial processing of the acquired data, if this pre-processing step helped to improve clarity of the ridges. The fingerprint mass images (TIC or non-TIC normalised were then shared using ZendTo with a fingerprint expert at West Yorkshire Police who assigned a Scotland Yard grade to each one of them. For training purposes a subset was used by the model, whereas for testing purposes, these scores remained blind to the AI team. The fingerprint mass images were organised in folders according to the grade a assigned and a selection was shared blind with the AI team for testing purposes. The fingermark images underwent further pre-processing and enhancement prior to using them with the model. This included techniques such as image filtering, wavelet analysis, and minutiae extraction, as detailed in the Data Pre-processing & Enhancement section of the project documentation. These pre-processing steps ensured that the images were consistently prepared for machine learning training. The images were then organized into categorized datasets (0-5) based on grading provided by West Yorkshire Police. These were then used for training the AI models, as outlined in the Dataset Information section (Data level Information document).