Signal transducer and activator of transcription3 (Stat3) plays a role in human cancers. One of the main approaches towards inhibiting its activity is the development of phosphopetides or peptidomimetics that competitively bind to the SH2 domain of Stat3. This work reports, to the best of our knowledge, the first computational molecular docking study to model all of the 142 peptidomimetics that mimic the Stat3 inhibitory pTyr-X-X-Glu motif. We used the docking programs AUTODOCK and VINA to model SH2 domain-peptidomimetic complexes and estimate their binding affinities. We obtained better screening accuracy using AUTODOCK which ranked the most potent inhibitor as second highest. Experimental binding energy values and scores from docking programs correlated poorly, confirming the limitations of many current docking programs when dealing with ligands that have a large number of rotatable bonds. Nevertheless, for close to 65% of peptidomimetics, the structures of complexes computed by AUTODOCK are in agreement with current understanding of the structures. Modeling of the SH2 domain-peptidomimetic complexes is essential to better understand and design drug compounds for curing cancer. Our study is an important first step forward towards that goal.