Proteases, especially MMPs, are attractive biomarkers given their central role in both physiological and pathological processes. Distinguishing MMP activity with degradable substrates, however, is a difficult task due to overlapping substrate specificity profiles. Here, we developed a system of peptomers (peptide-peptoid hybrids) to probe the impact of non-natural residues on MMP specificity for a MMP peptide consensus sequence. Peptoids are non-natural, N-substituted glycines with a large side chain diversity. Given the presence of a hallmark proline residue in the P3 position of MMP consensus sequences, we hypothesized that peptoids may offer N-substituted alternatives to generate differential interactions with MMPs. To investigate this hypothesis, peptomer substrates were exposed to five different MMPs, as well as bacterial collagenase, and monitored by fluorescence resonance energy transfer and liquid chromatography-mass spectrometry to determine the rate of cleavage and the composition of degraded fragments, respectively. We found that peptoid residues are well-tolerated in the P3 and P3' substrate sites and that the identity of the peptoid in these sites displays moderate influence on the rate of cleavage. However, peptoid residues were even better tolerated in the P1 substrate site where activity was more strongly correlated with sidechain identity than sidechain position. All MMPs explored demonstrated similar trends in specificity for the peptomers but exhibited different degrees of variability in proteolytic rate. These kinetic profiles served as "fingerprints" for the proteases and yielded separation by multivariate data analysis. To further demonstrate practical application of this tunability in degradation kinetics, peptomer substrates were tethered into hydrogels and released over distinct timescales. Overall, this work represents a significant step toward the design of probes that maximize differential MMP behavior and presents design rules to tune degradation kinetics with peptoid substitutions, which has promising implications for diagnostic and prognostic applications using array-based sensors.