Lameness in dairy cows is a concern for both producers and consumers. Milk mid-infrared (MIR) analysis could be an extra tool in the detection of lameness problems for farmers. Th e aim of this study was to test the feasibility of detecting lameness problems using MIR spectra from milk through the development of predictive models. Th e data for this research was provided by RINDERZUCHT AUSTRIA (2017), from their "Effi cient Cow" project and were recorded between July 2014 and December 2014. Th

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... data sets used were the complete data set of 9811 records and subsets according to lactation stage, parity, breed and hoof disease. Two types of pre-processing were tried: fi rst derivative followed by a Standard Normal Variate (SNV) transformation or second derivative followed by a SNV transformation. Th e fi rst and second derivatives do not give the same results which highlights the importance of pre-processing during model development. Th e best results were obtained for the Heel horn erosion subset. However, the specifi c nature of the used data requires the addition of more data coming from varied animals and farms and validation steps before using this technology on a larger scale. ACKNOWLEDGEMENTS I am grateful to EMR (2017) for giving me the opportunity to do this research. I would also like to thank RINDERZUCHT AUSTRIA (ZAR) for providing the data.