###### Abstract  
This study presents multi-response optimization and prediction tribological behaviors polytetrafluoroethylene (PTFE) matrix composites. For multi-response optimization, the Taguchi model was hybridized with grey relational analysis to produce grey relational grades (GRG). A support vector regression (SVR) model was combined with novel Harris Hawks' optimization (HHO) and swarm particle optimization (PSO) models to form hybrid SVR-HHG and SVR-PSO models to predict the GRG. The prediction ability of the models was appraised using the coefficient of determination (R\({}^{2}\)), correlation coefficient (R), mean square error (MSE), root mean square (RMSE), and mean absolute percentage error (MAPE). The results of the multi-response optimization revealed that the optimal combination of parametric values of GRG for minimum tribological rate was 9 N-1000 mesh-0.14 ms\({}^{-1}\)-55 m (L3G1 SD3 SS3). An analysis of variance of the GRG showed that a grit size of 94.56% was the most significant parameter influencing the tribological behavior of PTFE matrix composites. The validation results revealed that an improvement of 52% in GRG was achieved. The prediction results of all models showed that the SVR-PSO and SVR-HHG models were superior to the SVR model. Furthermore, the SVR-HHG model produced superior prediction error and the best goodness of fit over the SVR-PSO model. These findings concluded that hybrids models are promising tools in the multi-response optimization and prediction of tribological behaviors of PTFE matrix composites. They can serve as a guide in the design and development of tribological materials. P 2022 20  
lightweight, load bearing, and tribological conditions. For tribological applications, it has been shown that it PMCs are potential candidates in abrasive conditions [4; 5]. For PTFE matrix composites, it is generally agreed that increasing the fibre content might improve or weaken its tribological behaviors [6; 7]. PMCs with better tribological behaviors are used as brakes and clutches in automobiles and aircrafts [8; 9]. PTFE continues to receive attention in tribological conditions for its low coefficient of friction, ease of processability, chemical inertness, low density, and low cost [10; 11]. A frequent problem that occurs in industries is abrasive tribology. Many authors have experimentally studied the abrasion of polymer matrices and PMCs. For example, [PERSON] and [PERSON] [4] added nano-clay and discontinuous carbon fibre to a PA66/PP matrix. Different behaviors were observed on the addition of the reinforcements. Nano-clay-reinforced PA66/PP composite indicated better abrasion compared to carbon-reinforced PA66/PP composite [4]. [PERSON] and [PERSON] [12] studied the abrasion behaviors of different polymers and found that the polymers exhibited different abrasion behaviors. Moreover, it was revealed that distance was the most significant parameter influencing the abrasion behavior [12]. [PERSON], [PERSON], [PERSON], and [PERSON] [13] investigated the abrasive wear of vinyl/ester matrices reinforced with glass and carbon fabric reinforcements. The results showed that vinyl/ester strengthened with carbon fabric demonstrated a lower tribological rate than glass-reinforced vinyl/ester composite [13]. As reported by [PERSON] et al., in particles filled with ultra-high molecular weight polyethylene (UHMWPE) matrix composites, the improvement of the abrasion property was attributed to the particles' stiffness; in terms of the experimental parameter, it was found that applied load was the most significant parameter [14]. In their study of the coefficient of the friction and abrasion behavior of epoxy reinforced with betelnut filler, [PERSON], [PERSON], and [PERSON] [15] found that sliding the composites against coarser grains led to the maximum tribological rate. Similarly, mass loss increased when sliding velocity maximum [15]. The above illustrates experimental studies that seem to be tedious and cumbersome.