How to add raw (frequentist) estimates to forest plot

Question

Let's say I want to add raw point estimates with 95% confidence intervals to forest plot. What's the best way to achieve that? Here's a simple example of creating a forest plot (without frequentist/raw estimates):

import bambi as bmb
import pandas as pd
import arviz as az

df_simple = pd.DataFrame({
    'x': ['A', 'B', 'C'],
    'y': [10, 20, 30],
    'n': [100, 100, 100]
})

m = bmb.Model('p(y, n) ~ 0 + x', data=df_simple, family='binomial')
idata = m.fit(cores=4)

m.predict(idata)

az.plot_forest(idata, var_names='p(y, n)_mean', combined=True)