One way to decide which model fits best to your data, is to you use the Mean Squared Error (MSE). The model with lowest MSE can be considered the best fitting model. However, there is more to it. For example, how many parameters more does the better fitting model have compared to the other models. You would want the best fitting model with the fewest parameters. Also MSE is just one Metric to measure the goodness of fit.