Banana crops represent a collection of individual plants that vegetatively propagate at their own rhythm, with stabilised but unsynchronized production of inflorescences over time. Such agrosystems cannot be simulated with existing crop models due to the unsynchronized behavior of individual plants. A new simulation model (SIMBA-POP), based on the cohort population concept, was built to predict phenological patterns of the population and harvest dynamics in banana cropping systems. The model was calibrated and validated for Musa spp., 'AAA' group, cv. 'Cavendish Grande Naine' with field data from the French West Indies (Guadeloupe and Martinique). It can quite accurately predict temporally-varying banana harvesting dynamics (date and number of harvested bunches). The harvesting peak is predicted with a precision less than 3 weeks for the first 3 cropping cycles. The model structure is based on two linear chains of cohorts characterized by both physiological age (heat unit accumulation) and development-stage dispersion in the banana population due to flowering, harvesting and sucker selection. This model is a valuable tool for both farmers (field management) and crop scientists (to simulate and design cropping systems). This approach is a first step towards long-term simulation in non-synchronized agrosystems that cannot be simulated with existing crop models.