A failure in the behavior of safety-critical systems such as Unmanned Aerial Vehicles (UAV) may lead to hazards and serious consequences. Therefore UAVs must perform correctly throughout their intended life cycle. However, the functional system specification is not sufficient to ensure proper performance.The assessment of non-functional reliability, safety, or timing requirements in the early development phases helps to prevent conceptually wrong decisions. UAVs usually contain complex and tightly coupled hardware and software components that influence each other. Hence, a holistic approach to analyze the non-functional properties is preferable. The concept of phased mission systems enables the specification of individual requirements for different phases. This allows more accurate predictions of the success or failure of a mission.This paper presents a holistic model-based dependability assessment approach that supports system-software co-engineering for UAVs. The approach combines stochastic timing analysis and the data error propagation analysis and enables the consideration of phase-specific requirements as well as the identification, formalization, and analysis of timing properties. The solution proposed in this paper is centered around the Systems Modeling Language (SysML) and the systematic transformation of annotated SysML models to Probabilistic Model Checking (PMC) accessible Markov chain models.