This chapter describes a computational strategy for generating synthetic hormone concentration time series that accurately reproduce: (1) the types of temporal patterning observed in empirical studies examining pulsatile hormone release, and (2) the distribution and magnitudes of uncertainties encountered in experimental determinations of hormone concentrations in unknown samples. The model is constructed in a manner, to facilitate embodying the types of quantitative relationships frequently used to characterize endocrine secretory activity. Because endocrine systems appear to communicate information by intermittent secretory bursts rather than direct modulation of continuous secretory activity, analysis, and interpretation of experimentally determined hormone concentration time-series profiles often require quantitative consideration of complex temporal patterns. Pulse simulator provides a mechanism for recreating as realistically as possible the temporal patterning of peak locations and amplitudes of hormone concentration time series observed in actual empirical studies. The model is thus, defined within the context of the same quantifiable properties commonly elucidated from analysis of real data that are used to interpret time-dependent behavior of hormone secretory activity. The pulse simulator described in the chapter has incorporated within it a specific mechanism for superimposing variability on and providing uncertainty estimates for individual concentration time points, which realistically reflect the actual distribution and magnitude of uncertainty expected from hormone concentration determinations carried out in the experimental setting.