Choosing the best model from among different "best" models

A parsimonious model is a model that accomplishes a desired level of explanation or prediction with as few predictor variables as possible. For model evaluation there are different methods depending on what you want to know. There are generally two ways of evaluating a model: Based on predictions and based on goodness of fit on the current data. In the first case you want to know if your model adequately predicts new data, in the second you want to know whether your model adequatelly describes the relations in your current data. Those are two different things.