Researchers have developed many models to predict and understand human performance in text entry. Most of the models are specific to a technology or fail to account for human factors and variations in system parameters, and the relationship between them. Moreover, the process of fixing errors and its effects on text entry performance has not been studied. Here, we first analyze real-life text entry error correction behaviors. We then use our findings to develop a new model to predict the cost of error correction for character-based text entry technologies. We validate our model against quantities derived from the literature, as well as with a user study. Our study shows that the predicted and observed cost of error correction correspond well. At the end, we discuss potential applications of our new model.