In today's industrial landscape, wireless technology is gaining importance. Popular standards like WirelessHART, ZigBee, and ISA100.11a are widely used. Despite their benefits, wireless networks can experience packet loss or drops, making closed-loop systems vulnerable and resulting in system failure. To prevent such issues, dead-time compensation is necessary. Conventional techniques like predictive PI are commonly used for this purpose. However, these compensators may perform poorly for wireless networks with long dead time and variations in set-point, which can affect network stability. To address this, a fractional calculus-based predictive PI compensator is proposed in this paper for wireless networks in process industries, which can improve the performance of these compensators. The performance of the proposed compensator is evaluated on the industrial processes, including pressure, flow and temperature, where the measurement and control actions are carried out wirelessly. The wireless network’s performance is evaluated for packet loss, reduced throughput, and increased latency. The proposed compensator outperformed traditional ones in terms of achieving better set-point characteristics.