Single-Photon Avalanche Diode (SPAD) are used for Time-of-Flight (ToF) sensors to determine distance from a target by measuring the travel time of an emitted pulsed signal. These photodetectors work by triggering an avalanche of charge carriers upon photon absorption, resulting in a substantial amplification which can be detected. However, they are subject to spurious triggering by parasitic generated charge carriers, quantified as Dark Count Rate (DCR), which can compromise the accuracy of the measured distance. Therefore, it is crucial to identify and eliminate the potential source of DCR. To tackle this issue, a simulation methodology has been implemented to assess the DCR. This is achieved by simulating the avalanche breakdown probability, integrated with the carrier generation rate from defects. The breakdown probability can be simulated either in a deterministically, based on electric-field streamlines, or stochastically, by means of drift-diffusion simulation of the random carrier path. This methodology allows for the identification of the potential sources of pre-stress DCR by comparing simulation results to experimental data over a wide range of voltage and temperature. To ensure the accuracy of distance range measurements over time, it is necessary to predict the DCR level under various operating conditions. The aforementioned simulation methodology is used to identify the potential sources of post-stress DCR by comparing simulation results to stress experiments that evaluate the principal stress factors, namely temperature, voltage and irradiance. Furthermore, a Monte-Carlo study has been conducted to examine the device-to-device variation along stress duration. For an accurate Hot-Carrier Degradation (HCD) kinetics model, it is essential to consider not only the carrier energy distribution function but also the distribution of Si−H bond dissociation energy distribution at the Si/SiO2 interface. The number of available hot carriers is estimated from the carrier current density according to the carrier energy distribution simulated by means of a full-band Monte-Carlo method. The impact-ionization dissociation probability is employed to model the defect creation process, which exhibits sub-linear time dependence due to the gradual exhaustion of defect precursors. Accurate distance ranging requires distinguishing the signal from ambient noise and the DCR floor, and ensuring the target’s accumulated photon signal dominates over other random noise sources. An analytical formula allows to estimate the maximum distance ranging using the maximum signal strength, ambient noise level, and confidence levels. The impact of DCR can be estimated by considering the target’s reflectance and the ambient light conditions. In a nutshell, this work makes use of a in-depth characterization and simulation methodology to predict DCR in SPAD devices along stress duration, thereby allowing the assessment of its impact on distance range measurements.