In this manuscript, a multi-scale analysis combining the statistical analysis of the chip compression ratio and micro-scale evaluations of chip morphology was conducted. The individual and combined effects of spindle speed, feed, and depth of cut on the chip compression ratio were determined through experimental and statistical analysis methods. An uncoated carbide tool insert was used for machining operations, while natural olive oil was used for cutting fluid. The study used a full factorial design, analysis of variance, regression analysis, statistical modelling, graphical evaluation, and microstructural evaluation. The analysis of variance results showed that the parameters with the greatest influence on chip compression ratio were the feed and depth of cut, whereas spindle speed had a relatively minor impact. Increasing the feed reduced the chip compression ratio, while increasing the depth of cut had the opposite effect. The developed regression model demonstrated strong forecasting ability, with a high correlation among the R-sq, R-sq (adj), and R-sq (pred) values. Microstructural observations revealed a strong correlation between chip compression ratio reduction and chip morphology transition from continuous to segmented forms. Based on the combined statistical and microstructural analyses, depth of cut and feed were identified as the two dominant machining parameters governing the chip compression ratio and deformation mechanisms in minimum quantity of lubrication turning of AISI 1045. The study found that the influence of the minimum quantity of lubrication medium on the chip compression ratio at low feed and depth of cut values is significantly stronger, while its effectiveness is reduced in aggressive cutting modes.