For 3D sensor networks to monitor the ocean, forest and aerosphere, etc., sensors can forward their data to the base station by greedy routing. It is critical to quantitatively greedy routing’s deliverability for evaluating network’s functionality and performance. The probability that all sensors can successfully send their data to the base station by greedy routing is usually modeled as the probability of guaranteed delivery. For a typical spherical cap 3D sensor network deployment scenario where nodes follow a homogeneous Poisson point process, the relationship between the sensor transmission radius and the probability of guaranteed delivery is studied, and a tight analytical upper bound on the sensor transmission radius to ensure the designed deliverability probability is derived in this paper. The correctness and tightness of the derived upper bound are verified by extensive simulations. For 3D sensor networks to monitor the ocean, forest and aerosphere, etc., sensors can forward their data to the base station by greedy routing. It is critical to quantitatively greedy routing’s deliverability for evaluating network’s functionality and performance. The probability that all sensors can successfully send their data to the base station by greedy routing is usually modeled as the probability of guaranteed delivery. For a typical spherical cap 3D sensor network deployment scenario where nodes follow a homogeneous Poisson point process, the relationship between the sensor transmission radius and the probability of guaranteed delivery is studied, and a tight analytical upper bound on the sensor transmission radius to ensure the designed deliverability probability is derived in this paper. The correctness and tightness of the derived upper bound is verified by extensive simulations.