Roads are valuable assets worldwide that must be kept in good condition with minimum maintenance to safeguard against accident. From the literature review and the field observations, it is quite evident that geo-fields are one of the parameters which is responsible for damaging the road surface and hence further increasing the possibility of accidents. Present study is an attempt to provide a detailed insight into the performance of the road segment when subjected to geo-fields. For the same accident data of the Mumbai-Pune expressway, over six years from 2016 to 2021 has been used. Based on this data 46 accident black spots were segregated for investigation. An automated method is used to measure the pavement roughness index (PRI). On these spots, the quality of pavement is determined using the non- destructive test of Ultra Sonic Pulse Velocity (UPV). Geo-fields are measured in terms of electric and magnetic fields at these black spots. Data has been analyzed using Karl Pearson's correlation coefficient and linear regression models are developed for the average number of road accidents (Ā) with respect to PRI, UPV and Geo-fields. The mathematical models developed may provide a useful link between road accidents, geo-fields, and pavement surface conditions. It will also help transport authorities not only to predict the number of accidents at particular spots envisaged on existing expressway but will also enable them to design pavements appropriately for the detrimental effects of weak electric and magnetic fields. © 2022 Elsevier Ltd. All rights reserved.