Numerous cut-points exist to measure physical activity by accelerometry. The ability to compare accelerometer findings from different devices from different locations may be advantageous to researchers. This study aimed to develop and validate cut-points for 1.5, 3, and 6 METs in five activity monitors simultaneously. Fifty-six participants (mean age=39.9 [+/- 11.5]years) performed six activities while wearing a CosMED K4b(2) and five activity monitors: activPAL3 Micro, activPAL, ActiGraph GT1M, ActiGraph wGT3X-BT, and GENEActiv. Receiver operating characteristic curves and analysis were used to develop and validate cut-points for the vertical axis counts (all activity monitors) and sum of the vector magnitude (ActiGraph wGT3X-BT and GENEActiv) for 15second (all devices) and 60second (ActiGraph devices) epochs. A random coefficients statistical model was used to derive MET predictive equations for all activity monitors. Bland-Altman plots examined the variability in device error. No 1.5 MET cut-points were developed for the activPAL devices. All developed cut-points had high levels of sensitivity and specificity. When cross-validated in an independent group, high levels of sensitivity and specificity remained (77.4%, monitor and intensity dependent). The mean bias based on the Bland-Altman plots ranged from -0.03 METs to 0.35 METs (monitor dependent). This is the first study to develop and validate cut-points for five activity monitors simultaneously with high levels of sensitivity and specificity (77.4%). This is potentially a step toward cross-comparison/harmonization of data; however, further validation in a free-living environment is warranted.