Predicted values and marginal probability in pglm

I want predict a fitted values of a probit model for a data panel. My model is:

m.random<- pglm(formula = pooled,
                 index = c("code","Year"),
                 data = data_modelo,
                 family = binomial('probit'),
                 model = "ramdon",
                 method = "bfgs",R = 5)

The predict command doesn't help me, it says there is no applicable method to 'predict' applied to an object of class "c ('maxLik', 'maxim')" . The margins command also does not estimate the marginal probabilities. Can someone help me with command or techniques to predict the values and estimate the marginal probability?

Is this a typographical error in your code, or only in this posting?

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