Maternal smoking during pregnancy (MSDP) is a significant risk factor for the development of foetal, neonatal, and childhood morbidities. We hypothesized that infants exposed to MSDP have a distinct proteomic expression in their term placentas compared to infants without such an exposure. A total of 39 infants exposed (cord blood cotinine levels of >1ng/ml) and 44 infants not exposed to MSDP were included in the study. Women with chronic disease, body mass index of >30, or a history of uterine surgery were excluded. Total proteome abundance was analysed with quantitative mass spectrometry. For univariate analysis of differences in placental protein levels between groups, ANOVA with multiple testing corrections by the Benjamini-Hochberg method was used. For multivariate analysis, we used principal component analysis, partial least squares, lasso, random forest, and neural networks. The univariate analyses showed four differentially abundant proteins (PXDN, CYP1A1, GPR183, and KRT81) when heavy and moderate smoking groups were compared to non-smokers. With the help of machine learning, we found that an additional six proteins (SEPTIN3, CRAT, NAAA, CD248, CADM3, and ZNF648) were discriminants of MSDP. The placental abundance of these ten proteins together explained 74.1% of the variation in cord blood cotinine levels (p = 0.002). Infants exposed to MSDP showed differential abundance of proteins in term placentas. We report differential placental abundance of several proteins for the first time in the setting of MSDP. We believe that these findings supplement the current understanding of how MSDP affects the placental proteome.