Abstract: This study recognized, the differences in wealth and socio-economic status of households and investigated, the implication of wealth categories on improved soybean technology adoption and use intensity decisions of households. It combined qualitative data collected through key informants wealth ranking technique and quantitative data collected using structured questionnaire administered to 307 soybean-growing households randomly selected from five villages in Kaduna and Kano states of Northern Nigeria. Data were analyzed using descriptive and inferential statistics and regression techniques. Results revealed that 41.37, 46.58 and 12.05% of respondents were classified into the poor, middle class and rich categories, respectively. Descriptive analysis showed that significant differences existed in farm size, means of transport ownership and number of resident adult women between the rich and the middle class and middle class and poor households (p<0.01). Also, differences in yield were revealed between the rich and the poor (p<0.01) and middle class and poor households (p<0.05) in farming experience between rich and middle class and the middle class and poor households (p<0.05) in labour expenses between rich and middle class (p<0.05) and the rich and poor households (p<0.01). Regression analysis identified labour expenses as influencing adoption and use intensity decisions of all households and households of different wealth categories. Aside, it revealed that different set of variables influenced adoption behaviours for different wealth categories; level of commercialization and ownership of means of transport were specific determinants for the rich; number of residence adult women, extension services and yield were specific for the middle class while extension services and price were unique for the poor class of farmers. All factors, except level of commercialization for the rich had significant (p<0.05) positive influence on adoption and use intensity behaviours of households. Coefficients of elasticity show that total responsiveness of adoption and use intensity was highly elastic (ε>1) with respect to level of commercialization, labour expenses and ownership of means of transport for the rich, resident adult women and yield for the middle class and labour expenses, extension services and price for the poor farmer categories. When decomposed, results showed that marginal changes in all factors increased the probability of use intensity than they increased the probability of adoption for all wealth categories and all households. The study revealed the growing importance of use of paid labour for farming activities of all categories of households in the study area. The implication of the finding is that wealth classes of households is imperative and should be considered when introducing a crop-improvement technology in an area.