Nowadays, with the rapid expansion of Internet of Things (IoT) net-works, extending device battery lifetime has emerged as a paramount challenge. The 3GPP Narrowband IoT (NB-IoT) standard introduces advanced power-saving mechanisms, notably Power Saving Mode (PSM) and extended Discontinuous Reception (eDRX), designed to enhance device energy efficiency. However, achieving optimal energy savings necessitates a comprehensive evaluation of energy consumption under varying traffic conditions and configuration parameters. This paper proposes a stochastic Petri net (SPN) model to rigorously analyze the energy dynamics of NB-IoT devices, providing system designers with a robust analytical tool for performance evaluation and energy optimization. The model accurately reflects real-world device behavior by integrating Radio Resource Control (RRC) states, stochastic uplink and downlink traffic patterns, and critical 3GPP timer settings to simulate battery drain scenarios. Performance analyses conducted across diverse traffic loads and configurations of PSM intervals and eDRX cycles enable the quantification of energy consumption and the identification of optimal parameter settings to maximize battery lifetime. Validation results confirm the model’s effectiveness, particularly in characterizing mean sojourn times across operational states. Ultimately, this approach empowers NB-IoT system designers to tailor configurations that balance power efficiency with performance requirements, thereby facilitating the deployment of more sustainable IoT networks. While the model provides valuable insights for device-level parameter tuning under idealized conditions, future extensions should address dynamic traffic patterns, network-level effects, and broader empirical validation to enhance real-world applicability.