Under the H2020 project iSQAPER, 29 sites with min-till and 12 with no-till practices were identified across 7 and 5 pedoclimatic zones, respectively. These fields/plots were paired with nearby control fields/plots, sharing similar farming features but cultivated using topsoil inversion tillage. All plots were georeferenced and in 2016 a visual soil assessment (VSA), with a convenient score system (poor, moderate and good), of various components of soil quality was conducted on the soils of all fields/plots, complemented by measurements of soil organic matter, labile organic carbon content, pH and texture. Climate variables and indices (mean annual temperature, precipitation and potential evapotranspiration, aridity index, net primary production potential, and Gorczyński Continentality Index) were estimated using the software New_LocClim_1.10 for all locations. No-till fields/plots have a statistically significant higher proportion of good scores (p<0.05, chi-square test) with respect to soil structure and consistency, soil porosity, soil stability (slake test), and susceptibility to wind and water erosion when compared to control fields/plots; the strength of the effect, given by Crámer’s V for these VSA indicators, being V=0.85, 0.51, 0.43 and 0.43 respectively. The min-till group shows no statistically significant differences in VSA indicator scores with control fields/plots. Measured soil properties show no statistical difference between both conservation tillage groups and respective control groups. Due to an insufficient number of no-till sites further statistical analysis was performed only for the min-till and control groups. Spearman’s rank-correlation coefficients between VSA indicator scores and climate variables, within each group (min-till and control), show important differences between the two groups with respect to soil structure and consistency, porosity and colour. Correlation coefficients between VSA indicators scores and soil properties also show important differences between the two groups, especially the correlations of the VSA indicators soil structure and consistency, porosity, colour, susceptibility to erosion, and surface ponding, with one or more measured soil properties. We used Spearman’s rank-correlation to detect potential interactions between climate variables and soil properties, by calculating the correlations with VSA indicator scores within min-till and control groups. The potential interactions detected are distinct between min-till and Control. Despite the small sample (n=29 per group and missing data for some variables reduced n further (e.g. for soil organic matter n=13)), exploratory analysis using Linear Discriminant Analysis, show that an important error reduction in the scoring classification, in comparison to a random classification (prediction of the VSA indicators’ scores), can be achieved for most VSA indicators with few variables and/or interactions (e.g. presence of tillage pan, n=18, we achieved an error reduction of 83.3%, using penetration resistance and mean annual temperature as explanatory variables). We argue that min-till practices effects on VSA indicators scores, although not statistically different from those with conventional tillage, may have, at particular locations, a less negative impact on soil quality and soil conservation than conventional topsoil inversion practices; we also argue that a dataset with a higher number of records would allow the development of equations to accurately predict the effect of conservation tillage (no-till and min-till) and conventional tillage practices (topsoil inversion) on VSA indicator scores.