Visual hallucinations (VH) are difficult to treat because pharmacological interventions are only partially effective and associated with many adverse effects. One of the alternative non-pharmacological treatments for VH is repetitive transcranial magnetic stimulation (rTMS). However, identifying optimal stimulation sites for rTMS is challenging. To determine whether a connectivity-based targeting approach based on resting state (rs) fMRI data can be used to identify regions that may serve as effective rTMS targets. We acquired rs-fMRI scans pre-rTMS and post-rTMS in a single patient with retinitis pigmentosa (near blindness), Parkinson’s disease (PD) and had therapy-resistant VH. Rs-fMRI data were analyzed using fast Eigenvector Centrality Mapping (ECM). A target area was selected based on high ECM values and relative accessibility for rTMS. Subsequently, the patient was stimulated with 1 Hz rTMS during 5 days, followed by 30 Hz theta-burst stimulation during another 5 days. Distributions of surrogate and bootstrap data were used to statistically evaluate the effect of rTMS. The bilateral supplementary motor areas (SMA) were selected as rTMS target areas. When pre-rTMS were compared to post-rTMS, different ECM values were found in the SMA, precuneus, occipital pole and hippocampus. Clinical evaluation and follow-up showed that the intensity and frequency of the VH were decreased after rTMS. Our connectivity-based targeting approach applied to rs-fMRI data seems to be successful in identifying an optimal target area for rTMS on a single subject basis. Our results show changes in the connectivity pattern, both in the target area and associated hubs involved in VH pathogenesis.