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This work presents the design, analysis, and experimental validation of a novel chip-based 3-D printed ultra-high frequency (UHF) radio frequency identification (RFID) sensor designed for leaf moisture detection for smart farming applications. The presented sensor is designed to operate at a frequency of 915 MHz and utilizes an integrated circuit (IC) chip having a specified impedance of 18.06−j164 Ω at 915 MHz. The proposed sensor is fabricated by the state-of-the-art Nano Dimension DragonFly IV 3-D printer. The 3-D printer uses both dielectric and conductive inks in a single printer for producing additive manufactured electronics (AME). The performance of the sensor is validated by experiments conducted on Valley Oak, Japanese tree lilac, and Crabapple leaf samples. The sensor’s functionality is based on its ability to detect variations in the dielectric properties of leaves, which are caused by changes in moisture content. This is achieved by analyzing the radio frequency (RF) backscattered signal, measured in terms of the received signal strength indicator (RSSI) levels, using a standard RFID reader. Experimental results demonstrate a consistent linear relationship between RSSI levels and leaf moisture content that is used to obtain a calibration curve that can accurately determine unknown moisture levels. By integrating advanced fabrication techniques with reliable RF sensing mechanisms, this work offers a sustainable, and scalable solution for monitoring plant health and optimizing agricultural productivity.