In this thesis, we develop a numerical framework to simulate flow cytometry readings on BD FACSCanto flow cytometer by constructing cell profiles with specific target biomarker concentrations and modelling various physical phenomena involved in a flow cytometer. The principal aim of this thesis is to provide realistic datasets over which prospective automated compensation algorithms can be evaluated. In our study, we have first constructed model cell profiles based on human lymphocytes stained with fluorescent dyes. We secondly focused on determining the number of photons emitted from each fluorochrome-conjugated target proteins in a cell through fluorescence following excitation. We thirdly simulated the optic channel of BD FACSCanto flow cytometer and implemented a stochastic photon counting method to determine fluorescence intensity received in the different detectors. Then, we simulated a pre-amplifier circuit to calculate the detector responses as voltage pulses from each cell in response to received photons. Using the completed platform, we have generated a two-colour flow cytometry dataset including + +, + -, - +, and - - cell groups using FITC and PE fluorochromes. We demonstrated the usefulness of the generated reference datasets by applying two different linear compensation methods and comparing the resulting compensated datasets in both linear and logarithmic scales. These results suggest that the developed platform can be used to generate realistic multi-colour flow cytometry datasets that can be used to validate compensation algorithms.