<p>Optimizing the frequency and nature of maintenance on industrial equipment is the primary goal of the field of study known as Predictive Maintenance (PDM). New challenges and avenues in PDM have drawn the attention of many researchers towards the risk management strategy that may contribute to the success of PDM implementation. This paper aims to conduct a risk assessment in Predictive Maintenance 4.0 (PDM 4.0). In the 1st phase, risk factors were identified and analysed through a systematic literature review and expert opinions. In the 2nd phase, risk evaluation was conducted by the integrated approach of Best Worst Method (BWM) and Fuzzy Proximity Index Value (FPIV) methods. In the proposed integrated approach, risk criteria were identified through a literature review, and their weights were determined using the BWM. The final risk ranking of these criteria has been tabulated by FPIV, a novel MCDM method. A comparison was made between MCDM approaches, Fuzzy COPRAS and FPIV for risk ranking. Rank reversal and sensitivity analysis were performed to check the robustness of the integrated approach. The proposed models are illustrated with a real-world case study involving an online vibration monitoring system in a fertilizer organization using high-speed rotary machines. The results of the integrated approach demonstrate that high investment costs, inadequate vendor industry experience, inadequate training programs about PDM 4.0, inadequate modelling techniques, and regulatory &amp; legal risks, are the top five risks that need to be mitigated by practical methodology.</p>