The identification of sustainable fuels that exhibit optimal physicochemical properties, can be synthesized from widely available feedstocks, enable cost-effective large-scale production, and integrate seamlessly with existing infrastructure is essential for reducing global carbon emissions. Given their high energy density, efficient handling, and versatility across applications, renewable liquid fuels remain a critical component of even the most ambitious energy transition scenarios. Lactones, cyclic esters derived from the esterification of hydroxycarboxylic acids, feature a ring structure incorporating both a carbonyl group (C=O) and an ether oxygen (O). Variations in ring size and carbon chain length significantly influence their physicochemical properties, which in turn affect their performance in internal combustion engines. According to predictive models based on artificial neural networks, valerolactone, caprolactone, and helptalactone isomers show promise as fuels in spark-ignition engines due to their high octane (RON and MON) values. In this study, three lactones were tested in a spark-ignition co-operative fuel research (CFR) single-cylinder engine as blends (5%, 10% and 20% v/v) with isooctane and compared against baseline iso-octance to determine their impact on engine performance and emissions. CFR engine operating conditions set at 900 RPM and 70 kPa load with three compression ratio evaluated of 9:1, 11:1 and 13:1. Equivalence ratio sweeps are performed from the lean flammability limit to the phi = 1.2 at maximum brake torque spark timings. Key emissions parameters are presented include unburned hydrocarbon (UHC), combustion efficiency, nitrogen oxide emissions (NOx), carbon dioxide (CO2) and carbon monoxide (CO). The results indicate that both gamma-valerolactone, gamma-caprolactone, and gamma-helptalactone do not adversely affect the power output, stability, and emissions of the engine.