Application of any measurement requires reliable error estimates; this is particularly the case when meteorological observations are assimilated into numerical weather prediction models. Radio occultation measurement errors vary considerably between different observations. It is therefore desirable to estimate these errors dynamically on a profile-to-profile basis. In this study it is demonstrated that fluctuations in the full spectrum inversion (FSI) log amplitude can be mapped into profiles of error standard deviations for FSI retrieved bending angles on a profile-to-profile basis without using any external data. The performance of this technique is assessed by applying it to simulated GPS radio occultation signals sampled at 50 Hz with both severe additive noise and significant phase noise. In both cases, good agreement between predicted error profiles and the "true" error profiles is achieved. Comparisons between power spectra of predicted errors and "true" errors also show good agreement. However, a small part of the simulated signals is distorted by aliasing due to the downsampling to 50 Hz, which affects bending angles retrieved for a narrow range of impact parameters. For these bending angles, the predicted errors are too small as compared with the "true" errors. This shows that the proposed technique cannot predict errors related to poor signal acquisition.