Using branching processes to describe data generated with the Smith-Martin model of cell kinetics. Fitting discrete-time branching process (BP) models to a dataset generated with the homogeneous Smith-Martin (SM) model. The dataset comprise 104 cells in the A phase at time zero, and the total numbers in each generation (i.e. in both A and B phases) at days 2 and 4. We used SM parameter values λ = 0.5, Δ = 1/3 day (8 hours) and μ = 0.1. Two choices of uniform timestep gave reasonable fits – 12 hours (upper panels) and 16 hours (lower panels). We fitted several branching process models for all choices of timestep and in each case the best fit was a homogeneous model with constant probabilities of division and death. The 16 hour timestep gave the best fit (log likelihood (12h timestep) =426; -log likelihood (16h timestep) = 112), with γ = 0.239 and α = 0.064 being the estimated probabilities of division and death in each 16 h time interval respectively.