From the definition of your 420,2048 matrix, I guess that you have recorded
1024 points in the direct dimension with complex => 2048 points
For the 420 number I guess that you 210 increments in the in-direct dimension?
When you refer to FID number 60, I guess that increment 60 has gone wrong, and all 1024 points are rubbish.
Is this the case?
If this is the case, I do not believe that Forward or Backward prediction can help you.
There is no information on how the wave should look like.
If just some of the 1024 points are rubbish, then you might have luck with linear prediction.
If the whole increment 60 is rubbish, then it can be seen as your dataset is sparse.
"non-uniformly sampled NMR data cannot be processed directly using fast Fourier transform (FFT)"
And Linear Prediction is not made for this.
In qMDD, you can transform your spectrum defining that FID 60 is "gone".
Then either reconstruct with FT (Zero filling), or reconstruct the missing FID, from nearby information (CS Compressed sensing).
In our Lab we routinely use qMDD for recording sparse 3D data.
We think it is well working, with a easy GUI, and easy to process.
We have tried several NLS software, and qMDD is by far the easiest we have tried yet.
The output format is nmrPipe, which should be possible to convert to Felix.