While there is significant interest in the use of COTS multicore platforms for Real-time Systems, there has been very little in terms of practical methods to calculate the interference multiplier (i.e. the increase in execution time due to interference) between tasks on such systems. COTS multicore platforms present two distinct challenges: firstly, the variable interference between tasks competing for shared resources such as cache, and secondly the complexity of the hardware mechanisms and policies used, which may result in a system which is very difficult if not impossible to analyse; assuming that the exact details of the hardware are even disclosed! This paper proposes a new technique, Forecast-Based Interference analysis, which mitigates both of these issues by combining measurement-based techniques with statistical techniques and forecast modelling to enable the prediction of an interference multiplier for a given set of tasks, in an automated and reliable manner. The combination of execution times and interference multipliers can be used both in the design, e.g. for specifying timing watchdogs, and analysis, e.g. verifying schedulability.