The goal of this study was to determine the nature and factors influencing smallholder farmers in their adoption decision-making regarding the use of soil conservation practices introduced by extension practitioners in South Africa, using the case of farming at Qamata Irrigation Scheme, Eastern Cape. Using a central argument (thesis statement), the study argued that an adequate understanding and definition of smallholder farmers’ adoption decision-making process is very crucial to solving the problem of soil erosion/ degradation problem amongst smallholder farmers. Adopting the case study research design, information from 70 crop farmers (in a farmer focus group interviews) form the basis of the study. Basic models of analysis were the multiple, probit and logit, as well as the binary logistic regression analyses. According to the empirical results, perception was found very relevant in adoption decision-making, interacting positively and significantly with eight of the seventeen adoption variables chosen for the study. The indication therefore is that age (p<0.050), education (p<0.0030), and marriage (p<0.036), have more potentials to improve farmers’ perception. Similarly, higher farmer incomes (from crops [p<0.017], off-farm [p<0.038] and overall [p<0.011] income) also have a likelihood to improve farmers’ perception regarding soil conservation, for improved adoption. Further indication is that farmers who are aware (p<0.015) of the soil practices introduced by extension are also those who participate in their use (p<0.041). Employing the binary logistic, probit and logit regression models, results suggest that the nature of adoption decision-making processes of smallholder farmers is complex (not straight), being influenced by multiple factors. While age (p<0.099), gender (p<0.031), total income (p<0.081) impacted positively significant on smallholder farmers’ adoption decision-making, marital status (p<0.025), sources of land (p<0.063), length of continuously farming on same piece of land (p<0.013), and level of crop production (p<0.002) impacted negatively. The indication therefore was that older farmers preferred their own practices to the recommended practices by extension, which is in line with literature. Also as expected, more females preferred their own practices to extension recommended, while more males preferred the recommended practices. Similarly, marriage, land ownership, farming continuously on a spot for a long period, as well as increase in the level of crop production, all had a propensity to influence farmers toward the adoption of extension recommended practices as against farmers’ practices. Further results indicate, that farmers’ education (p<0.032), household size (p<0.37), and income (off-farm [p<0.036] and total [p<0.004]), measures used to measure farmers’ livelihood standards in the study, were positively significant in association with adoption. The indication was that, adoption decision-making is potentially capable of improving education level of farmers; increase the size of household, thus providing easy family labour; and as well improve level of income for the farmer. Based on the foregoing, the suggestion therefore is that any technology intervention programme that will succeed must begin with a clear understanding and analysis of farmers’ adoption process. This is better achieved when the adoption process is seen as a four-stage process, where the farmer first forms a view about the innovation (perception stage), and then decides whether or not to use it (adoption stage), as well as how much of the innovation to adopt (level of adoption stage), and finally how much is this innovation going to affect my livelihood (impact of adoption stage). Also, due to the particular relevance of perception in the adoption decision-making process, technology disseminators (extension), researchers and policy makers alike must never conclude on the rejection of any technology, not until factors determining perception of individuals have been well studied. The notion here is that, even at the confirmation stage of the adoption process of an individual adopter, when a rejection is confirmed, for an example, analysing factors of the adopter’s perception at play at the particular time of the innovation in question, could go a long way to redirecting the course of the adoption process of the said individual.