Why do I receive this numpy error when using statsmodels to predict test values?

I am getting an error when trying to use statsmodels .predict to predict my test values.

Code:

X_train, X_test, y_train, y_test = train_test_split(X_new_np, y, test_size=0.2, random_state=42)
logit = sm.Logit(y_train, X_train)
reg = logit.fit_regularized(start_params=None, method='l1_cvxopt_cp', maxiter= 1000, full_output=1, disp=1, callback=None, alpha=.01, trim_mode='auto', auto_trim_tol=0.01, size_trim_tol=0.0001, qc_tol=0.03)
reg.summary()
y_pred_test = logit.predict(X_test)

Error:

ValueError: shapes (1000,61) and (251,61) not aligned: 61 (dim 1) != 251 (dim 0)

You simply don't predict from the right object. reg is the one that was fitted, you should then use reg.predict. The following code runs without error (I used your fit_regularized parameters).

from sklearn.model_selection import train_test_split
import numpy as np
from statsmodels.api import Logit

x = np.random.randn(100,50)
y = np.random.randint(0,2,100).astype(bool)

print(x.shape, y.shape)

X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=.2)

logit = Logit(y_train, X_train)
reg = logit.fit_regularized(start_params=None, method='l1_cvxopt_cp',
        maxiter= 1000, full_output=1, disp=1, callback=None,
        alpha=.01, trim_mode='auto', auto_trim_tol=0.01,
        size_trim_tol=0.0001, qc_tol=0.03)
print(reg.summary())
y_pred_test = reg.predict(X_test)