A modulation-based index is proposed for predicting speech intelligibility by cochlear implant (CI) listeners. The input to the proposed index are speech envelopes extracted using the individual CI user's daily strategy, and as such, this approach incorporates information about the number of active electrodes, shape of the compression function and electrical dynamic range. High correlation (r = 0.96) was achieved with the proposed index when evaluated with speech-reception thresholds (SRTs) obtained by CI users in steady and speech-masker conditions. This outcome suggests that the information contained in electrodograms seems to be sufficient for reliably predicting CI user's performance in noise. The proposed index can be used by clinicians to optimize the selection of fitting parameters of individual CI users for better performance in noise.