Heat input regulation is crucial for deposition quality in laser metal deposition (LMD) processes. To control the heat input, melt pool temperature is regulated using temperature controllers. Part I of this paper showed that, although online melt pool temperature control performs well in terms of tracking the temperature reference, it cannot guarantee consistent track morphology. Therefore, a new methodology, known as layer-to-layer temperature control, is proposed in this paper. The idea of layer-to-layer temperature control is to adjust the laser power profile between layers. The part height profile is measured between layers, and the temperature is measured online. The data are then utilized to identify the parameters of a LMD process model using particle swarm optimization. The laser power profile is then computed using iterative learning control, based on the estimated process model and the reference melt pool temperature of the next layer. The deposition results show that the layer-to-layer temperature controller is capable of not only tracking the reference temperature, but also producing a consistent track morphology.