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ABSTRACT Unmanned aerial vehicles (UAVs) are revolutionizing a wide range of military and civilian applications. Since mission failures caused by malfunctions of UAVs can incur significant economic losses, modeling and ensuring the reliability of UAV‐based mission systems is a crucial area of research with challenges posed by multiple dependent phases of operations and collaborations among heterogeneous UAVs. The existing reliability models are mostly applicable to single‐UAV or homogeneous multi‐UAV systems. This paper advances the state of the art by proposing a new analytical modeling method to assess the reliability of a multi‐phased mission performed by heterogeneous collaborative UAVs. The proposed method systematically integrates an integral‐based Markov approach with a binary decision diagram‐based combinatorial method, addressing inter‐ and intraphase collaborations as well as phase‐dependent configurations of heterogeneous UAVs for accomplishing different tasks. As demonstrated by a detailed analysis of a two‐phase rescue mission performed by six UAVs, the proposed method has no limitations on UAV's time‐to‐failure and time‐to‐detection distributions. Another contribution is to formulate and solve UAV allocation problems, achieving a balance between mission success probability and total cost. Given the uncertainties inherent in the mission scenario, the random phase duration problem is also examined.