Stem cells contribute to organismal homeostasis by balancing division, self-renewal and differentiation. Elucidating the strategies by which stem cells achieve this balance is critical for understanding homeostasis, and for addressing pathogenesis associated with the disruption of this balance (e.g., cancer). Mathematical models have been developed to distill the principles underlying adult stem cell dynamics in vertebrates. Yet, valuable insights can be derived from modeling invertebrate stem cell systems that rely on a fundamentally different strategy. Here, integrating experimental, computational, and analytical approaches, we develop a quantitative model that reveals basic principles of clonal growth of individual neoblasts – pluripotent planarian stem cells. Deriving key physiological parameter values from experimental data, we show that neoblast colony growth can be well described as a straightforward stochastic decision process, without assuming memory or communication among cells. Crucially, by experimentally suppressing differentiation to major lineages, we reveal the interplay between colony growth and lineage decisions. Our findings suggest that neoblasts pre-select their progenitor lineage based on an underlying cell fate distribution, and that arresting differentiation into specific lineages disrupts neoblasts’ proliferative capacity – without inducing compensatory expression of other lineages. Our findings uncover essential aspects of stem cell regulation in planarians, demonstrating how principles distinct from those of vertebrate models can lead to robust homeostatic mechanisms.