Predefined Neural Networks instead of fine tuning?
It depends. If you are doing a task for which the weights of a very large network, trained on the same type of problem, are present, then it's better to use the weights of that pre-trained network. You can also fine tune the layers later on. One such example is the VGG16 Net. This NN was used in the ImageNet challenge in 2014, hence if you are trying to do image classification tasks where your images are the subset of ImageNet, then you should use the pre-trained VGG16 weights. This is a great tutorial if you want to go in details.

But the above situation might not be true in every case. For example, the above case is not true if you reverse the situation.