This study aimed at determining the current level of group membership and the determinants of farmers’ decision to join farmers’ groups in Uganda. Using multistage and simple random sampling techniques, we collected data from 374 maize farmers in Kiryandongo district, western Uganda. Data collection involved interviews between the trained enumerators and the farmers. Data were then entered into SPSS template and then transferred to Stata version 13 for analysis. Chi – square and ttest were used to compare group participants and non -group participants while binary logistic regression model was used to determine the determinants of farmers’ decision to join groups respectively. The results showed that only 45% of the farmers belonged to farmers’ groups. A further comparison of group participants and non-participants showed that group participants were generally better off than their counterparts. Additionally, the results from binary logistic model showed that five predictors had a positive and statistically significant relationship with farmers’ decision to join farmers’ groups. These included education level (p<0.01), farm size (p<0.05), access to credit (p<0.01), access to extension services (p<0.01) and farm location (p<0.01). To increase the level of group membership among the farmers, more extension agents should be employed by the government. These agents should reach all the farmers and disseminate information on the benefits of joining farmer groups. Farmers should also be encouraged to access agricultural credit from various sources in order to join groups.

Keywords: Group membership, Binary logit, farm productivity, Uganda.