This study presents the development and characterization of 2D ferroelectric field-effect transistors (2D FeFETs) using nanoscale ferroelectric HfZrO₂ (HZO) and 2D semiconductors, specifically SnS₂. The fabricated devices demonstrated multi-level data storage capabilities and successfully emulated essential biological characteristics such as excitatory/inhibitory postsynaptic currents (EPSC/IPSC), Pair-Pulse Facilitation (PPF), and Spike-Timing Dependent Plasticity (STDP). Extensive endurance tests confirmed robust stability, excellent linearity, and high C_max/G_min ratios, all crucial for realizing multi-level data states (>7-bit operation). The device achieved a pattern recognition accuracy of approximately 94% on the Modified National Institute of Standards and Technology (MNIST) handwritten dataset when integrated into a neural network, highlighting its potential in neuromorphic systems. The 2D FeFETs exhibited sub-fermtojoule (48 aJ/spike) and fast response (1 μs) characteristics, which are 10^4 times faster than human synapses (≈10 ms). The research underscores the potential of nanoscale ferroelectric and 2D materials in advancing the next generation of artificial intelligence technologies.This study presents the development and characterization of 2D ferroelectric field-effect transistors (2D FeFETs) using nanoscale ferroelectric HfZrO₂ (HZO) and 2D semiconductors, specifically SnS₂. The fabricated devices demonstrated multi-level data storage capabilities and successfully emulated essential biological characteristics such as excitatory/inhibitory postsynaptic currents (EPSC/IPSC), Pair-Pulse Facilitation (PPF), and Spike-Timing Dependent Plasticity (STDP). Extensive endurance tests confirmed robust stability, excellent linearity, and high C_max/G_min ratios, all crucial for realizing multi-level data states (>7-bit operation). The device achieved a pattern recognition accuracy of approximately 94% on the Modified National Institute of Standards and Technology (MNIST) handwritten dataset when integrated into a neural network, highlighting its potential in neuromorphic systems. The 2D FeFETs exhibited sub-fermtojoule (48 aJ/spike) and fast response (1 μs) characteristics, which are 10^4 times faster than human synapses (≈10 ms). The research underscores the potential of nanoscale ferroelectric and 2D materials in advancing the next generation of artificial intelligence technologies.