예시문제 작업형2 test 데이터 예측시 발생하는 오류

안녕하세요! 복습하는 도중에 이런 에러가 발생되어 질문드립니다 ㅠㅠ

import pandas as pd
X_train = pd.read_csv('X_train.csv',encoding="euc-kr")
y_train = pd.read_csv('y_train.csv')
X_test = pd.read_csv('X_test.csv',encoding="euc-kr")

print(X_train.shape,y_train.shape)
# X_train.head()
# y_train.head()

# X_train.info()  #X_train 환불금액 결측치, 오브젝트 두개 
# y_train.info()

X_train = X_train.fillna(0)
X_train.isnull().sum()

X_train = X_train.drop(['cust_id'],axis=1)
cust_id = X_test.pop('cust_id')

#라벨인코딩 
from sklearn.preprocessing import LabelEncoder 
cols = X_train.select_dtypes( include = 'object').columns
cols
for col in cols : 
    le = LabelEncoder()
    X_train[col] = le.fit_transform(X_train[col])
    X_test[col] = le.transform(X_test[col])

X_train.head()

#검증데이터 분리 
from sklearn.model_selection import train_test_split
X_tr, X_val, y_tr, y_val = train_test_split(X_train,
                                            y_train['gender'],
                                            test_size = 0.2,
                                            random_state = 2022)
X_tr.shape, X_val.shape, y_tr.shape, y_val.shape

#모델링 - 랜덤포레스트
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import roc_auc_score

model = RandomForestClassifier(random_state=2022)
model.fit(X_tr,y_tr)
pred = model.predict_proba(X_val)


roc_auc_score(y_val,pred[:,1])

pred = model.predict_proba(X_test) <------------------이 과정에서 발생되는 오류입니다
pred

ValueError: Input X contains NaN. RandomForestClassifier does not accept missing values encoded as NaN natively.

라는 에러가 발생합니다 ㅠㅠ

코드를 검토해봐도 이상은 없는거같은데.. 뭐가문제일까요? ㅠㅠ