<p>Plasmonic photonic crystal fiber (PPCF)-based multiparameter sensors generally detect two or more physicochemical quantities. In many applications, these sensors are preferred over single-parameter counterparts owing to their real-time capabilities in parallel and distributed sensing schemes. PPCF multiparameter sensors operate through two fundamental mechanisms, the first of which is based on direct refractive index (RI) sensing. The second mechanism is based on the principle of transduction. This paper presents an in-depth analysis of key optical characteristics of PPCFs in the context of multiparameter sensor optimization, covering effective material and mode confinement losses, fiber birefringence, polarization mode dispersion, intermodal dispersion, chromatic dispersion, and inter-core crosstalk. A comprehensive examination of how these phenomena influence the trade-offs among sensitivity, selectivity, and repeatability is given. Mathematical frameworks for modeling critical performance parameters are also presented. A review of plasmonic materials, including metallic alloys, semiconductors, transition metals, and metamaterials for high-throughput multiparameter sensing, is provided. The paper further classifies PPCF multiparameter sensor architectures into three major categories, namely RI and temperature, magnetic field (MF) and temperature, as well as RI, temperature, and MF sensors, and evaluates their performance metrics. Finally, the paper addresses current research gaps, design challenges, and directions for future research, emphasizing integration with artificial intelligence (AI), the internet of things (IoT), and nanophotonics.</p>