Knowledge of the habitat requirements and suitable breeding areas of sea birds is crucial for their management and conservation. However, there are still few studies that have modelled the breeding distribution and abundance of colonial sea birds. In this study, we created predictive distribution models for a colonial species, the arctic tern Sterna paradisaea, using 14 environmental variables calculated for 525 islands in the Archipelago Sea in SW Finland. We modelled the occurrence (presence-absence) using generalised additive models (GAMs) and abundance (pair numbers/colony size) using hurdle models fitted with GAM. We tested for spatial autocorrelation in model residuals and evaluated the models on independent data. Critical factors influencing the occurrence of the arctic tern were the proportions of boulder or gravel and forest of island area, as well as island maximum elevation and area, such that the species seemed to prefer large and low islands with sparse vegetation. Abundance was influenced by the proportions of boulder or gravel and bare rock of island area, as well as exposure and island area. To some extent, different factors influenced the occurrence and the abundance. The evaluation results of the models were good, with an AUC value of 0.91 for the most accurate presence-absence model and a Pearson's correlation coefficient of 0.60 for the most accurate hurdle model. The predictive ability of the models increased when we removed islands with single or few breeding pairs from the data set. Although the hurdle models did not produce accurate pair number estimates, they indicated which islands are suitable for larger colonies. Abundance is a crucial factor for colonial species. This modelling technique can therefore be of great value for the conservation and management of the arctic tern and similar colonial species.