cross validation for small dataset
Given the size of your data set, the best approach to cross validation is the 
Leave-One-Out method. You haven't discussed the language or package you used for your model, but generally speaking you set the $k$ equal to the number of records.  In your case, that 39.  This will cause your model to train on 38 instances and predict the 39th, with each instance eventually will receive a classification.