•JET real-time disruption predictor with metallic wall 991 discharges analyzed.•Predictor training has been carried out with JET C wall data.•Success, false alarm and missed alarm rates are 98.4%, 0.9% and 1.6%, respectively.•Alarms are triggered in average 426ms before the disruption. The impact of disruptions in JET became even more important with the replacement of the previous Carbon Fiber Composite (CFC) wall with a more fragile full metal ITER-like wall (ILW). The development of robust disruption mitigation systems is crucial for JET (and also for ITER). Moreover, a reliable real-time (RT) disruption predictor is a pre-requisite to any mitigation method. The Advance Predictor Of DISruptions (APODIS) has been installed in the JET Real-Time Data Network (RTDN) for the RT recognition of disruptions. The predictor operates with the new ILW but it has been trained only with discharges belonging to campaigns with the CFC wall. 7 real-time signals are used to characterize the plasma status (disruptive or non-disruptive) at regular intervals of 32ms. After the first 3 JET ILW campaigns (991 discharges), the success rate of the predictor is 98.36% (alarms are triggered in average 426ms before the disruptions). The false alarm and missed alarm rates are 0.92% and 1.64%.