Despite significant advancements in recent decades, gaining a comprehensive understanding of brain computations remains a significant challenge in neuroscience. Using computational models is crucial for unraveling this complex phenomenon and is equally indispensable for studying neurological disorders. This endeavor has created many neuronal models that capture brain dynamics at various scales and complexities. These models range from highly detailed multi-compartmental models like the Hodgkin-Huxley model to simpler models like the leaky integrate-and-fire model. However, most existing models do not account for the potential influence of glial cells, particularly astrocytes, on neuronal physiology. This gap persists even with the emerging evidence indicating their critical role in regulating neural network activity, plasticity, and even neurological pathologies. While some literature focuses on modeling interactions between neurons and glial cells, these approaches are often sophisticated, mimicking the complexity of the physiological phenomenon. In our work, we aim to propose a simplified tripartite synapse model encompassing the presynaptic neuron, postsynaptic neuron, and astrocyte. This model is more straightforward yet still includes the primary astrocytic calcium dynamics. We defined the tripartite synapse model based on the Adaptive Exponential Integrate-and-Fire neuron model and a simplified scheme of the astrocyte model previously proposed by Postnov. Our results demonstrate the model’s ability to replicate essential synaptic transmission dynamics attributed to astrocytic calcium dynamics within the context of the tripartite synapse. Through our simulations, we propose that astrocytes can modify and shape the behavior and can introduce irregularities in the firing pattern of both presynaptic and postsynaptic neurons.