As widely expected, Peter Higgs was awarded the Nobel Prize in Physics for predicting the existance of a particle (or better, a mechanism) that breaks the symmetry of massless particles, like photons, and massive particles, like quarks. He only had to wait five decades for the Large Hadron Collider to be built (and collect data this past year confirming the existance of the Higgs Boson) in order to claim his prize. This is an extreme example of the ability of the human mind to predict theoretically what cannot be achived experimentally for a long time.
In chemistry, the prize was awarded for the development of quantum chemistry techniques that allow the simulation of complicated molecles, including enzymes. Before, simulating these systems seemed intractable, since the reactions relied on quantum mechanics (which involves computationaly difficult calculations) for the active sites where electrons were jumping between molecules, but simulating entire macromoles would take way to much computing power. The laurates overcame this problem by breaking the simulation into regions where classical mechanics works fine (basically, outside the active site) and regions where the full computation was required. This hybrid model allow the best of both worlds: the accuracy of quantum mechanics when needed, and the computation speed when it’s not. This is a great example of model building – the key is usually figuring out what you can safely ignore. As the saying goes: “All models are wrong, some models are useful“