Hi I have a question about the out-of-sample prediction using multinomial logit model.

<Situation>
I have a cross-section data set including eleven countries.
Let the dependent variable be y (a nominal variable having three vaelus, 1, 2, and 3), and suppose that we only have two regressors, x1 and x2.

<What I want to show>
The response pattern of a choice probability of the alternative one corresponding to the changes in x1 is different in the 11th country

<What I have done>
First, I ran the multinomial logit regression using only the first ten countries like below (For simplicity, I do not write the details of options)
Code:
mlogit y x1 x2 if 1 <= country_id & country_id =< 10
Second, I predict the choice probability of the alternative one in the 11th country using the previous estimate for each value of x1 (from 0 to 5)
Code:
keep if country_id == 11
margins, at(x1=(0(1)5)) predict(outcome(1))
Third, I kept the sample means of a dummy of the alternative one
Code:
gen y1 = (y == 1)
summarize y1 if x1 == 0
summarize y1 if x1 == 1
.
.
summarize y1 if x1 == 5
Finally, I compared the predicted choice probability of alternative one to the sample means at each value of x1

The results show that the predicted choice probabilities are pretty different from the sample means at each x1 value.
Here, can I conclude that the response of choice probability are different in the 11th country? (Since we cannot well predict the choice probability in 11th country by using the other countries)

For simplicity, my explanation could be too simple.
I am sorry if you cannot understand what I'm saying.

Thank you for your time spending to read this question.