By using the alternate fuels, spark-ignition engines can significantly lower exhaust emissions. Producer gas (PG), produced through biomass gasification, is one of the most effective alternate fuel in gaseous form. However, employing neat PG to fuel SI engines results low power and efficiency. Hence, in this study, the novel approach of blending grape wood-based producer gas with propane as fuel has been investigated to increase the power and efficiency of SI engines with reducing pollutants. To accomplish this, quasi-dimensional thermodynamic modelling was employed with two-zone (burn and unburn zone) combustion model to simulate SI engine performance at 1500 rpm. Satisfactory model validation was observed by utilizing an experimental report and thereafter the simulation was run as per the Design of Experiment’s RSM strategy to envisage parametric impacts and confirm multi-objective optimization. To enhance the SI engine performance, equivalence ratio (ER), compression ratio (CR), ignition timing (IT), and propane blending fraction (BF) with PG were considered as parametric operating settings. Also, to determine best operating condition, an optimization was conducted with best response of performance regarding Brake-thermal efficiency (BTE), Brake-mean effective pressure (BMEP), Brake specific fuel consumption (BSFC), and emissions reduction of Carbon monoxide (CO), Nitrous monoxide (NO). Response regressions were modelled using ANOVA, and optimal output responses were predicted accurately using RSM-based response optimizer. The optimal responses were 27.47 % BTE, 7.51(bars) BMEP, 0.3153 (kg/kWh) BSFC and emissions of 1.16(V%) CO and 1407.5(ppm) NO, with an observed composite desirability of 0.859. The corresponding optimal independent operating parameters were 79.9 % BF, 1.032 ER, 13.99 CR and 41.428 (⁰BTDC-CA) IT. Moreover, to determine the minimum utilization of propane for best response of engine performance an additional case of multi-objective optimization revealed optimum BF to be 46.14 V%. Overall, it was found that blending and optimization strategies provided improvement in SI engine performance.