The L-H transition power threshold is often predicted using log-linear power laws fitted to experimental data. Here we present two methods aimed at improving such predictions for both future machines such as ITER and current machines such as JET. Extrapolation to future machines is addressed using Errors-in-Variables (EIV) techniques. Interpolative single machine prediction is addressed using Neural Networks (NNs).